├── .github └── workflows │ ├── repo_search.yml │ ├── repo_status.yml │ └── wiki_gen.yml ├── .gitignore ├── README.md ├── conf.py ├── generated_wiki ├── __init__.py ├── alternative_finance.md ├── colleges_centers_and_departments.md ├── courses.md ├── data.md ├── data_processing_techniques_and_transformations.md ├── deep_learning_and_reinforcement_learning.md ├── derivatives_and_hedging.md ├── extended_research.md ├── factor_and_risk_analysis.md ├── fixed_income.md ├── other_models.md ├── personal_papers.md ├── portfolio_selection_and_optimisation.md ├── reinforcement_learning.md ├── textual.md └── unsupervised.md ├── git_search.py ├── git_status.py ├── git_util.py ├── raw_data ├── __init__.py ├── process.drawio └── url_list.csv ├── requirements.txt └── wiki_gen.py /.github/workflows/repo_search.yml: -------------------------------------------------------------------------------- 1 | name: Repo-Search 2 | 3 | on: 4 | schedule: 5 | - cron: '0 1 * * *' 6 | 7 | jobs: 8 | # Set the job key. The key is displayed as the job name 9 | update-repo-status: 10 | # Name the Job 11 | name: Update repo status for all saved repo 12 | # Set the type of machine to run on 13 | runs-on: ubuntu-latest 14 | 15 | steps: 16 | - name: Checkout code 17 | uses: actions/checkout@v2 18 | with: 19 | fetch-depth: 0 20 | 21 | - name: setup python 22 | uses: actions/setup-python@v2 23 | with: 24 | python-version: 3.7 25 | 26 | - name: Install dependencies 27 | run: | 28 | python -m pip install --upgrade pip 29 | if [ -f requirements.txt ]; then pip install -r requirements.txt; fi 30 | 31 | - name: execute py script # run the run.py to get the latest data 32 | run: | 33 | python git_search.py 34 | env: 35 | GIT_TOKEN: ${{ secrets.GIT_TOKEN }} 36 | 37 | - name: Commit & Push changes 38 | uses: actions-js/push@master 39 | with: 40 | github_token: ${{ secrets.GIT_TOKEN }} 41 | branch: 'master' 42 | -------------------------------------------------------------------------------- /.github/workflows/repo_status.yml: -------------------------------------------------------------------------------- 1 | name: Repo-Updater 2 | 3 | on: 4 | schedule: 5 | - cron: '0 0 * * 0' # weekly 6 | 7 | 8 | jobs: 9 | # Set the job key. The key is displayed as the job name 10 | update-repo-status: 11 | # Name the Job 12 | name: Update repo status for all saved repo 13 | # Set the type of machine to run on 14 | runs-on: ubuntu-latest 15 | 16 | steps: 17 | - name: Checkout code 18 | uses: actions/checkout@v2 19 | with: 20 | fetch-depth: 0 21 | 22 | - name: setup python 23 | uses: actions/setup-python@v2 24 | with: 25 | python-version: 3.7 26 | 27 | - name: Install dependencies 28 | run: | 29 | python -m pip install --upgrade pip 30 | if [ -f requirements.txt ]; then pip install -r requirements.txt; fi 31 | 32 | - name: execute py script # run the run.py to get the latest data 33 | run: | 34 | python git_status.py 35 | env: 36 | GIT_TOKEN: ${{ secrets.GIT_TOKEN }} 37 | 38 | - name: Commit & Push changes 39 | uses: actions-js/push@master 40 | with: 41 | github_token: ${{ secrets.GIT_TOKEN }} 42 | branch: 'master' 43 | -------------------------------------------------------------------------------- /.github/workflows/wiki_gen.yml: -------------------------------------------------------------------------------- 1 | name: Wiki-Generator 2 | 3 | # generate wiki page on every push 4 | on: push 5 | 6 | jobs: 7 | # Set the job key. The key is displayed as the job name 8 | update-repo-status: 9 | # Name the Job 10 | name: Update repo status for all saved repo 11 | # Set the type of machine to run on 12 | runs-on: ubuntu-latest 13 | 14 | steps: 15 | - name: Checkout code 16 | uses: actions/checkout@v2 17 | with: 18 | fetch-depth: 0 19 | 20 | - name: setup python 21 | uses: actions/setup-python@v2 22 | with: 23 | python-version: 3.7 24 | 25 | - name: Install dependencies 26 | run: | 27 | python -m pip install --upgrade pip 28 | if [ -f requirements.txt ]; then pip install -r requirements.txt; fi 29 | 30 | # - name: execute status update script # run the run.py to get the latest data 31 | # run: | 32 | # python git_search.py 33 | # env: 34 | # GIT_TOKEN: ${{ secrets.GIT_TOKEN }} 35 | 36 | - name: execute wiki generation script # run the wiki_gen 37 | run: | 38 | python wiki_gen.py 39 | 40 | - name: Upload Documentation to Wiki 41 | uses: SwiftDocOrg/github-wiki-publish-action@v1 42 | with: 43 | path: "generated_wiki" 44 | env: 45 | GH_PERSONAL_ACCESS_TOKEN: ${{ secrets.GIT_TOKEN }} 46 | 47 | # - name: Check out master first 48 | # uses: actions/checkout@master 49 | # with: 50 | # persist-credentials: false # otherwise, the token used is the GITHUB_TOKEN, instead of your personal token 51 | # fetch-depth: 0 # otherwise, you will failed to push refs to dest repo 52 | 53 | - name: Commit & Push changes 54 | uses: actions-js/push@master 55 | with: 56 | github_token: ${{ secrets.GIT_TOKEN }} 57 | branch: 'master' -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | .idea/ 131 | 132 | .DS_Store 133 | .editorconfig 134 | -------------------------------------------------------------------------------- /conf.py: -------------------------------------------------------------------------------- 1 | import os 2 | PROJECT_ROOT_DIR = os.path.dirname(os.path.abspath(__file__)) 3 | -------------------------------------------------------------------------------- /generated_wiki/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/firmai/financial-machine-learning/a0fda6ac1f40251b9eb7cc32dd665db59130714e/generated_wiki/__init__.py -------------------------------------------------------------------------------- /generated_wiki/alternative_finance.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [Venture Capital NN](https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring) | Cox-PH neural network predictions for VC/innovations finance research. | nan | nan | nan | :heavy_check_mark: | | 4 | | [EDMarketConnector](https://github.com/EDCD/EDMarketConnector) | NEW | 2015-06-02 19:17:34 | 2024-09-24 23:28:42 | 988.0 | :heavy_check_mark: | | 5 | | [yahoofinancials](https://github.com/JECSand/yahoofinancials) | NEW | 2017-10-22 03:10:57 | 2023-12-17 07:54:07 | 910.0 | :heavy_check_mark: | | 6 | | [Watch Valuation](https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb) | Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued. | 2017-02-08 18:39:29 | 2017-04-27 22:55:55 | 9.0 | :heavy_multiplication_x: | | 7 | | [Kiva Crowdfunding](https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb) | Exploratory data analysis. | 2018-02-27 16:46:02 | 2019-02-13 00:15:27 | 7.0 | :heavy_multiplication_x: | | 8 | | [Venture Capital](https://github.com/julian-chan/etothex) | Insight into a new founder to make data-driven investment decisions. | 2017-12-04 08:59:44 | 2017-12-13 05:35:27 | 7.0 | :heavy_multiplication_x: | | 9 | | [botupdate](https://github.com/botupdate/botupdate) | NEW | 2019-07-01 20:22:44 | 2020-10-29 02:31:17 | 582.0 | :heavy_check_mark: | | 10 | | [VC OLS](https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb) | VC regression. | 2018-03-29 23:31:13 | 2018-03-29 23:33:19 | 4.0 | :heavy_multiplication_x: | | 11 | | [awesome-systematic-trading](https://github.com/edarchimbaud/awesome-systematic-trading) | NEW | 2022-02-05 20:48:52 | 2024-08-16 12:06:38 | 3783.0 | :heavy_check_mark: | | 12 | | [pitch_deck](https://github.com/joelparkerhenderson/pitch_deck) | NEW | 2016-09-17 01:30:26 | 2024-05-16 16:23:12 | 343.0 | :heavy_check_mark: | | 13 | | [pitch-deck](https://github.com/joelparkerhenderson/pitch-deck) | NEW | 2016-09-17 01:30:26 | 2024-05-16 16:23:12 | 343.0 | :heavy_check_mark: | | 14 | | [HomeHarvest](https://github.com/ZacharyHampton/HomeHarvest) | NEW | 2023-09-15 19:29:01 | 2024-09-06 22:49:07 | 314.0 | :heavy_check_mark: | | 15 | | [Private Equity](https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb) | Valuation models. | 2016-01-27 21:13:33 | 2016-03-14 20:03:52 | 22.0 | :heavy_multiplication_x: | | 16 | | [Art Valuation](https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb) | Art evaluation analytics. | 2014-12-11 00:25:39 | 2014-12-12 21:25:46 | 19.0 | :heavy_multiplication_x: | | 17 | | [Blockchain](https://github.com/nud3l/dInvest) | Repository for distributed autonomous investment banking. | 2016-09-05 19:12:40 | 2017-04-24 10:48:56 | 18.0 | :heavy_multiplication_x: | | 18 | | [realtime-forex-crypto-stock-tick-finance-websocket-api](https://github.com/alltick/realtime-forex-crypto-stock-tick-finance-websocket-api) | NEW | 2024-03-14 06:07:55 | 2024-09-18 10:16:09 | 147.0 | :heavy_check_mark: | | 19 | | [cot_reports](https://github.com/NDelventhal/cot_reports) | NEW | 2020-11-16 19:16:18 | 2023-12-29 23:14:53 | 120.0 | :heavy_check_mark: | | 20 | | [notebooks](https://github.com/tradingeconomics/notebooks) | NEW | 2020-11-13 13:39:37 | 2023-07-20 12:27:16 | 104.0 | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/colleges_centers_and_departments.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------|:------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------| 3 | | [NYU FRE](https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering) | Finance and Risk Engineering (NYU Tandon) | nan | nan | nan | :heavy_check_mark: | | 4 | | [Oxford Man](https://www.oxford-man.ox.ac.uk/) | Oxford-Man Institute of Quantitative Finance | nan | nan | nan | :heavy_check_mark: | | 5 | | [Berkeley Lab CIFT](https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/) | nan | nan | nan | nan | :heavy_check_mark: | | 6 | | [Cornell University](https://www.cornell.edu/) | nan | nan | nan | nan | :heavy_check_mark: | | 7 | | [NYU Courant](https://cims.nyu.edu/) | Courant Institute of Mathematical Sciences, New York University | nan | nan | nan | :heavy_check_mark: | | 8 | | [Stanford Advanced Financial Technologies](https://fintech.stanford.edu/) | Stanford Advanced Financial Technologies Laboratory | nan | nan | nan | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/courses.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [mlcourse.ai](https://github.com/Yorko/mlcourse.ai) | NEW | 2017-02-27 08:32:20 | 2024-08-25 08:08:31 | 9695.0 | :heavy_check_mark: | | 4 | | [datascience-box](https://github.com/rstudio-education/datascience-box) | NEW | 2017-12-29 22:16:17 | 2024-08-15 22:45:51 | 956.0 | :heavy_check_mark: | | 5 | | [machine-learning-zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp) | NEW | 2020-04-17 04:29:23 | 2024-09-24 09:02:07 | 9337.0 | :heavy_check_mark: | | 6 | | [datasci_course_materials](https://github.com/uwescience/datasci_course_materials) | NEW | 2013-04-12 05:54:36 | 2017-03-21 19:21:02 | 918.0 | :heavy_multiplication_x: | | 7 | | [ml-mipt](https://github.com/girafe-ai/ml-mipt) | NEW | 2022-09-01 16:16:05 | 2022-09-02 08:44:48 | 9.0 | :heavy_multiplication_x: | | 8 | | [ciml](https://github.com/hal3/ciml) | NEW | 2015-08-12 19:26:00 | 2017-01-20 16:24:19 | 888.0 | :heavy_multiplication_x: | | 9 | | [cornell-cs5785-applied-ml](https://github.com/kuleshov/cornell-cs5785-applied-ml) | NEW | 2021-03-26 06:33:58 | 2021-09-02 00:34:55 | 874.0 | :heavy_multiplication_x: | | 10 | | [ml-course-msu](https://github.com/esokolov/ml-course-msu) | NEW | 2015-09-11 08:51:24 | 2018-05-07 15:40:56 | 871.0 | :heavy_multiplication_x: | | 11 | | [Octave](https://github.com/schneems/Octave) | NEW | 2011-10-24 23:50:52 | 2016-07-08 20:45:40 | 824.0 | :heavy_multiplication_x: | | 12 | | [machine_learning_with_python_jadi](https://github.com/jadijadi/machine_learning_with_python_jadi) | NEW | 2021-09-20 08:19:48 | 2024-08-16 05:12:53 | 801.0 | :heavy_check_mark: | | 13 | | [DAT4](https://github.com/justmarkham/DAT4) | NEW | 2014-12-10 19:38:29 | 2021-02-15 23:26:27 | 794.0 | :heavy_multiplication_x: | | 14 | | [deploying-machine-learning-models](https://github.com/trainindata/deploying-machine-learning-models) | NEW | 2019-01-09 20:30:46 | 2023-04-19 17:15:38 | 790.0 | :heavy_check_mark: | | 15 | | [Algo Trading](https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading) | Intro to algo trading. | 2017-10-29 20:34:54 | 2019-01-22 06:56:08 | 79.0 | :heavy_multiplication_x: | | 16 | | [master](https://github.com/ML-course/master) | NEW | 2017-02-04 22:44:35 | 2024-04-01 10:09:20 | 784.0 | :heavy_check_mark: | | 17 | | [DataScienceSpCourseNotes](https://github.com/sux13/DataScienceSpCourseNotes) | NEW | 2015-03-09 00:51:32 | 2016-02-16 06:12:54 | 764.0 | :heavy_multiplication_x: | | 18 | | [DataScienceCourse](https://github.com/briandalessandro/DataScienceCourse) | NEW | 2014-10-01 08:45:51 | 2020-12-20 13:03:56 | 751.0 | :heavy_multiplication_x: | | 19 | | [causalML](https://github.com/altdeep/causalML) | NEW | 2018-12-17 05:22:47 | 2024-07-28 18:22:15 | 726.0 | :heavy_check_mark: | | 20 | | [machine-learning-course](https://github.com/instillai/machine-learning-course) | NEW | 2019-02-15 00:23:19 | 2020-04-21 03:19:12 | 7012.0 | :heavy_multiplication_x: | | 21 | | [stat479-machine-learning-fs19](https://github.com/rasbt/stat479-machine-learning-fs19) | NEW | 2019-08-07 07:36:20 | 2020-11-28 00:04:07 | 697.0 | :heavy_multiplication_x: | | 22 | | [python_ka_chilla2023](https://github.com/AammarTufail/python_ka_chilla2023) | NEW | 2022-12-29 21:05:56 | 2023-02-21 22:22:08 | 680.0 | :heavy_check_mark: | | 23 | | [ML Specialisation](https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization) | Machine Learning in Finance. | 2019-01-24 02:55:01 | 2020-01-03 21:54:16 | 67.0 | :heavy_multiplication_x: | | 24 | | [DAT3](https://github.com/justmarkham/DAT3) | NEW | 2014-09-18 20:30:19 | 2020-05-19 09:21:02 | 659.0 | :heavy_multiplication_x: | | 25 | | [competitive-data-science](https://github.com/hse-aml/competitive-data-science) | NEW | 2017-10-28 14:56:44 | 2020-06-13 13:44:26 | 647.0 | :heavy_multiplication_x: | | 26 | | [DP100](https://github.com/MicrosoftLearning/DP100) | NEW | 2020-01-06 20:38:41 | 2020-12-30 17:22:42 | 635.0 | :heavy_multiplication_x: | | 27 | | [ML-Course-Notes](https://github.com/dair-ai/ML-Course-Notes) | NEW | 2022-03-17 11:18:50 | 2023-02-13 03:38:54 | 6005.0 | :heavy_check_mark: | | 28 | | [dtu_mlops](https://github.com/SkafteNicki/dtu_mlops) | NEW | 2021-04-07 09:27:30 | 2024-08-09 09:10:24 | 574.0 | :heavy_check_mark: | | 29 | | [GML2023](https://github.com/xbresson/GML2023) | NEW | 2024-02-12 01:05:08 | 2024-08-27 06:06:36 | 572.0 | :heavy_check_mark: | | 30 | | [mlcourse](https://github.com/davidrosenberg/mlcourse) | NEW | 2015-10-11 22:18:25 | 2023-11-02 21:29:07 | 567.0 | :heavy_check_mark: | | 31 | | [course-resources-ml-with-experts-budgets](https://github.com/datacamp/course-resources-ml-with-experts-budgets) | NEW | 2017-03-02 13:10:27 | 2017-12-14 20:46:54 | 558.0 | :heavy_multiplication_x: | | 32 | | [Artificial-Intelligence-and-Machine-Learning](https://github.com/emilmont/Artificial-Intelligence-and-Machine-Learning) | NEW | 2011-10-16 22:51:06 | 2013-07-20 18:21:51 | 545.0 | :heavy_multiplication_x: | | 33 | | [serverless-ml-course](https://github.com/featurestoreorg/serverless-ml-course) | NEW | 2022-09-01 14:09:52 | 2024-09-24 20:48:47 | 529.0 | :heavy_check_mark: | | 34 | | [Stanford-Machine-Learning-Course](https://github.com/zhouxc/Stanford-Machine-Learning-Course) | NEW | 2011-12-25 10:00:48 | 2011-12-25 10:01:12 | 527.0 | :heavy_multiplication_x: | | 35 | | [geospatialdatascience](https://github.com/mszell/geospatialdatascience) | NEW | 2022-05-14 12:59:52 | 2022-11-02 08:27:01 | 515.0 | :heavy_check_mark: | | 36 | | [DataScience](https://github.com/JuliaAcademy/DataScience) | NEW | 2020-05-21 01:26:52 | 2022-10-01 13:34:26 | 490.0 | :heavy_check_mark: | | 37 | | [stat479-machine-learning-fs18](https://github.com/rasbt/stat479-machine-learning-fs18) | NEW | 2018-09-06 00:30:56 | 2018-12-20 23:45:13 | 489.0 | :heavy_multiplication_x: | | 38 | | [Quant-Finance-Resources](https://github.com/PyPatel/Quant-Finance-Resources) | NEW | 2019-08-12 15:19:22 | 2021-09-13 10:13:59 | 487.0 | :heavy_multiplication_x: | | 39 | | [Coursera-Stanford-ML-Python](https://github.com/mstampfer/Coursera-Stanford-ML-Python) | NEW | 2015-10-28 19:51:00 | 2016-09-02 00:21:30 | 444.0 | :heavy_multiplication_x: | | 40 | | [awesome-full-stack-machine-courses](https://github.com/leehanchung/awesome-full-stack-machine-courses) | NEW | 2019-10-31 19:26:14 | 2023-09-02 01:23:09 | 427.0 | :heavy_check_mark: | | 41 | | [coursera-machine-learning-engineering-for-prod-mlops-specialization](https://github.com/amanchadha/coursera-machine-learning-engineering-for-prod-mlops-specialization) | NEW | 2021-06-22 04:46:37 | 2023-06-30 05:03:32 | 426.0 | :heavy_check_mark: | | 42 | | [Introduction-to-Machine-Learning](https://github.com/codeheroku/Introduction-to-Machine-Learning) | NEW | 2019-02-09 12:07:52 | 2020-11-28 08:44:08 | 426.0 | :heavy_multiplication_x: | | 43 | | [Artificial-Intelligence-And-Data-Science-Pro](https://github.com/pranavanand24/Artificial-Intelligence-And-Data-Science-Pro) | NEW | 2020-05-12 07:34:21 | 2023-01-29 11:51:23 | 422.0 | :heavy_check_mark: | | 44 | | [courses](https://github.com/DataScienceSpecialization/courses) | NEW | 2014-01-21 10:22:57 | 2016-03-16 12:13:44 | 4050.0 | :heavy_multiplication_x: | | 45 | | [TradingView-neural-networks-Learning](https://github.com/darkness337/TradingView-neural-networks-Learning) | NEW | 2024-02-22 17:17:37 | 2024-02-24 16:57:13 | 405.0 | :heavy_check_mark: | | 46 | | [Basic Derivatives](https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives) | Basic forward contracts and hedging. | 2017-08-24 00:11:37 | 2017-10-13 01:32:23 | 4.0 | :heavy_multiplication_x: | | 47 | | [machine-learning-resources](https://github.com/datascienceid/machine-learning-resources) | NEW | 2018-04-09 15:10:08 | 2019-07-30 14:25:27 | 396.0 | :heavy_multiplication_x: | | 48 | | [Online-Courses-Learning](https://github.com/MrinmoiHossain/Online-Courses-Learning) | NEW | 2018-08-12 18:52:29 | 2019-07-14 21:07:56 | 391.0 | :heavy_multiplication_x: | | 49 | | [machine-learning-programming-assignments-coursera-andrew-ng](https://github.com/AvaisP/machine-learning-programming-assignments-coursera-andrew-ng) | NEW | 2016-08-20 18:05:22 | 2016-09-05 19:14:41 | 389.0 | :heavy_multiplication_x: | | 50 | | [MTH594_MachineLearning](https://github.com/diefimov/MTH594_MachineLearning) | NEW | 2016-03-09 07:35:19 | 2017-03-31 21:46:26 | 383.0 | :heavy_multiplication_x: | | 51 | | [stanford-CS229](https://github.com/ccombier/stanford-CS229) | NEW | 2018-07-30 20:19:32 | 2018-09-10 19:03:06 | 380.0 | :heavy_multiplication_x: | | 52 | | [Computational-Finance-Course](https://github.com/LechGrzelak/Computational-Finance-Course) | NEW | 2021-02-20 16:09:03 | 2024-03-01 11:58:38 | 369.0 | :heavy_check_mark: | | 53 | | [ml-workspace](https://github.com/AdicherlaVenkataSai/ml-workspace) | NEW | 2020-07-10 06:38:10 | 2021-09-03 07:21:14 | 369.0 | :heavy_multiplication_x: | | 54 | | [AdvancedML](https://github.com/sjhwang82/AdvancedML) | NEW | 2019-02-22 09:15:04 | 2022-11-25 10:53:47 | 366.0 | :heavy_check_mark: | | 55 | | [feature-engineering-for-machine-learning](https://github.com/solegalli/feature-engineering-for-machine-learning) | NEW | 2019-05-01 08:05:42 | 2023-12-05 12:07:06 | 366.0 | :heavy_check_mark: | | 56 | | [MLOps-Specialization-Notes](https://github.com/kennethleungty/MLOps-Specialization-Notes) | NEW | 2021-07-11 14:20:24 | 2023-05-17 16:28:29 | 351.0 | :heavy_check_mark: | | 57 | | [msds621](https://github.com/parrt/msds621) | NEW | 2019-07-01 18:21:25 | 2021-12-07 19:51:49 | 348.0 | :heavy_multiplication_x: | | 58 | | [machine-learning-notebooks](https://github.com/krasserm/machine-learning-notebooks) | NEW | 2017-07-24 10:21:05 | 2020-09-07 12:48:43 | 341.0 | :heavy_multiplication_x: | | 59 | | [machine-learning-online-2018](https://github.com/coding-blocks-archives/machine-learning-online-2018) | NEW | 2018-07-18 04:24:58 | 2020-07-02 09:24:40 | 340.0 | :heavy_multiplication_x: | | 60 | | [ai-developer-resources](https://github.com/duncantmiller/ai-developer-resources) | NEW | 2023-12-04 17:31:24 | 2024-05-09 04:24:25 | 332.0 | :heavy_check_mark: | | 61 | | [python-seminar](https://github.com/profjsb/python-seminar) | NEW | 2012-08-23 03:30:01 | 2022-04-25 22:56:48 | 325.0 | :heavy_multiplication_x: | | 62 | | [datacamp](https://github.com/ozlerhakan/datacamp) | NEW | 2018-07-20 09:19:43 | 2024-04-21 08:17:00 | 322.0 | :heavy_check_mark: | | 63 | | [2014](https://github.com/cs109/2014) | NEW | 2014-07-21 22:46:20 | 2014-12-17 14:37:02 | 318.0 | :heavy_multiplication_x: | | 64 | | [Machine-Learning-by-Andrew-Ng-in-Python](https://github.com/Benlau93/Machine-Learning-by-Andrew-Ng-in-Python) | NEW | 2018-12-06 02:20:59 | 2019-01-11 04:24:52 | 311.0 | :heavy_multiplication_x: | | 65 | | [coursera-deep-learning-specialization](https://github.com/amanchadha/coursera-deep-learning-specialization) | NEW | 2020-06-24 05:59:01 | 2024-04-13 01:45:25 | 3047.0 | :heavy_check_mark: | | 66 | | [Handson Python for Finance](https://github.com/PacktPublishing/Hands-on-Python-for-Finance) | Hands-on Python for Finance published by Packt. | 2018-08-20 14:10:37 | 2023-01-30 09:07:24 | 304.0 | :heavy_check_mark: | | 67 | | [PyMLSlides](https://github.com/dmitriydligach/PyMLSlides) | NEW | 2017-06-05 13:59:15 | 2021-10-07 17:34:18 | 303.0 | :heavy_multiplication_x: | | 68 | | [ML_Process_Course](https://github.com/PlayingNumbers/ML_Process_Course) | NEW | 2022-06-30 22:04:48 | 2023-06-21 18:39:45 | 297.0 | :heavy_check_mark: | | 69 | | [matrixcalc](https://github.com/mitmath/matrixcalc) | NEW | 2022-01-04 15:39:28 | 2024-02-09 17:17:51 | 297.0 | :heavy_check_mark: | | 70 | | [Data-Science-Free](https://github.com/frontbenchHQ/Data-Science-Free) | NEW | 2019-02-10 14:29:29 | 2020-07-13 06:36:25 | 295.0 | :heavy_multiplication_x: | | 71 | | [feature-selection-for-machine-learning](https://github.com/solegalli/feature-selection-for-machine-learning) | NEW | 2020-01-08 17:08:12 | 2024-04-27 16:24:40 | 290.0 | :heavy_check_mark: | | 72 | | [zero-to-mastery-ml](https://github.com/mrdbourke/zero-to-mastery-ml) | NEW | 2019-09-23 04:56:51 | 2024-09-25 06:05:55 | 2876.0 | :heavy_check_mark: | | 73 | | [tensorflow-without-a-phd](https://github.com/GoogleCloudPlatform/tensorflow-without-a-phd) | NEW | 2018-05-09 18:33:40 | 2020-06-03 21:08:32 | 2778.0 | :heavy_multiplication_x: | | 74 | | [mlbookcamp-code](https://github.com/alexeygrigorev/mlbookcamp-code) | NEW | 2023-08-01 14:02:25 | 2024-09-15 09:54:55 | 276.0 | :heavy_check_mark: | | 75 | | [machine-learning-andrew-ng](https://github.com/susilvaalmeida/machine-learning-andrew-ng) | NEW | 2019-03-15 23:51:58 | 2020-05-30 23:46:44 | 274.0 | :heavy_multiplication_x: | | 76 | | [awesome-ml-courses](https://github.com/luspr/awesome-ml-courses) | NEW | 2020-05-08 20:41:59 | 2024-06-18 07:14:47 | 2688.0 | :heavy_check_mark: | | 77 | | [MachineLearningWithPython](https://github.com/JerryKurata/MachineLearningWithPython) | NEW | 2016-04-24 21:20:10 | 2023-01-27 01:12:06 | 259.0 | :heavy_check_mark: | | 78 | | [stanford-cs231](https://github.com/machinelearningnanodegree/stanford-cs231) | NEW | 2016-09-05 01:40:41 | 2017-02-03 16:46:46 | 258.0 | :heavy_multiplication_x: | | 79 | | [iNeuron-Full-Stack-Data-Science-Assignments](https://github.com/amanovishnu/iNeuron-Full-Stack-Data-Science-Assignments) | NEW | 2021-05-31 10:46:57 | 2022-07-17 10:52:33 | 256.0 | :heavy_multiplication_x: | | 80 | | [TeachingDataScience](https://github.com/yogeshhk/TeachingDataScience) | NEW | 2019-04-13 23:43:45 | 2024-09-28 02:39:36 | 255.0 | :heavy_check_mark: | | 81 | | [PythonDataScienceFullThrottle](https://github.com/pdeitel/PythonDataScienceFullThrottle) | NEW | 2019-07-18 15:53:01 | 2024-08-13 13:38:57 | 253.0 | :heavy_check_mark: | | 82 | | [MachineLearning6.867](https://github.com/peteflorence/MachineLearning6.867) | NEW | 2015-09-08 16:25:19 | 2015-10-20 15:43:40 | 242.0 | :heavy_multiplication_x: | | 83 | | [365datascience](https://github.com/UsmanNiazi/365datascience) | NEW | 2020-04-12 12:01:18 | 2020-11-01 07:39:21 | 241.0 | :heavy_multiplication_x: | | 84 | | [Udemy---Machine-Learning](https://github.com/jmportilla/Udemy---Machine-Learning) | NEW | 2015-04-27 22:44:40 | 2016-07-06 23:58:33 | 238.0 | :heavy_multiplication_x: | | 85 | | [ML_RiskManagement](https://github.com/albahnsen/ML_RiskManagement) | NEW | 2016-05-16 19:37:52 | 2018-02-08 21:05:21 | 235.0 | :heavy_multiplication_x: | | 86 | | [Intro](https://github.com/rstudio/Intro) | NEW | 2014-11-11 20:45:33 | 2014-11-12 13:42:32 | 235.0 | :heavy_multiplication_x: | | 87 | | [JSE_OkCupid](https://github.com/rudeboybert/JSE_OkCupid) | NEW | 2015-03-28 08:38:27 | 2021-04-26 18:35:26 | 234.0 | :heavy_multiplication_x: | | 88 | | [Developing_Data_Products](https://github.com/DataScienceSpecialization/Developing_Data_Products) | NEW | 2016-08-25 19:47:39 | 2017-07-31 15:11:59 | 233.0 | :heavy_multiplication_x: | | 89 | | [julia-ml-course](https://github.com/adrhill/julia-ml-course) | NEW | 2023-04-24 15:17:08 | 2024-09-06 13:36:23 | 233.0 | :heavy_check_mark: | | 90 | | [DAT7](https://github.com/justmarkham/DAT7) | NEW | 2015-05-16 02:29:54 | 2016-03-18 16:20:30 | 231.0 | :heavy_multiplication_x: | | 91 | | [MachineLearning_Ng](https://github.com/HuangCongQing/MachineLearning_Ng) | NEW | 2017-10-14 13:06:55 | 2020-05-11 01:56:28 | 229.0 | :heavy_multiplication_x: | | 92 | | [qmlcourse](https://github.com/quantum-ods/qmlcourse) | NEW | 2021-03-06 04:19:25 | 2024-07-07 23:51:37 | 228.0 | :heavy_check_mark: | | 93 | | [Python-Learning](https://github.com/AmirHosseinBabaeayan/Python-Learning) | NEW | 2021-09-14 15:45:23 | 2023-09-16 20:43:57 | 226.0 | :heavy_check_mark: | | 94 | | [AmazonSageMakerCourse](https://github.com/ChandraLingam/AmazonSageMakerCourse) | NEW | 2019-04-02 16:31:20 | 2024-05-30 04:54:39 | 225.0 | :heavy_check_mark: | | 95 | | [machine-learning-coursera](https://github.com/yhyap/machine-learning-coursera) | NEW | 2013-05-03 09:41:53 | 2013-05-05 11:58:38 | 224.0 | :heavy_multiplication_x: | | 96 | | [datasciencecoursera](https://github.com/mGalarnyk/datasciencecoursera) | NEW | 2016-12-27 03:59:24 | 2021-02-19 04:16:58 | 2225.0 | :heavy_multiplication_x: | | 97 | | [dl-workshop](https://github.com/ericmjl/dl-workshop) | NEW | 2018-12-20 22:34:43 | 2022-05-14 19:09:02 | 222.0 | :heavy_multiplication_x: | | 98 | | [Machine-Learning-AndrewNg-DeepLearning.AI](https://github.com/azminewasi/Machine-Learning-AndrewNg-DeepLearning.AI) | NEW | 2022-07-24 11:14:14 | 2023-06-11 06:21:18 | 221.0 | :heavy_check_mark: | | 99 | | [supervised-ML-case-studies-course](https://github.com/juliasilge/supervised-ML-case-studies-course) | NEW | 2019-06-01 21:32:47 | 2021-08-22 23:19:32 | 221.0 | :heavy_multiplication_x: | | 100 | | [umich-eecs545-lectures](https://github.com/thejakeyboy/umich-eecs545-lectures) | NEW | 2016-01-24 18:46:16 | 2016-08-29 20:34:54 | 219.0 | :heavy_multiplication_x: | | 101 | | [ml-course](https://github.com/girafe-ai/ml-course) | NEW | 2019-02-01 16:20:39 | 2024-08-24 16:37:56 | 2186.0 | :heavy_check_mark: | | 102 | | [python_data_science_and_machine_learning_bootcamp](https://github.com/ccniuj/python_data_science_and_machine_learning_bootcamp) | NEW | 2017-01-15 12:05:12 | 2017-01-15 12:20:06 | 217.0 | :heavy_multiplication_x: | | 103 | | [Introduction-to-Data-Science-in-python](https://github.com/sidsriv/Introduction-to-Data-Science-in-python) | NEW | 2016-11-01 15:41:24 | 2017-01-22 10:28:21 | 216.0 | :heavy_multiplication_x: | | 104 | | [ml-intro](https://github.com/rolling-scopes-school/ml-intro) | NEW | 2020-11-27 14:55:34 | 2022-06-02 10:13:04 | 216.0 | :heavy_multiplication_x: | | 105 | | [Core-Machine-Learning-Course](https://github.com/ayush714/Core-Machine-Learning-Course) | NEW | 2023-04-12 03:09:33 | 2023-04-12 03:50:57 | 214.0 | :heavy_check_mark: | | 106 | | [creative_ml](https://github.com/acids-ircam/creative_ml) | NEW | 2023-03-16 07:08:54 | 2024-07-11 13:24:13 | 212.0 | :heavy_check_mark: | | 107 | | [MonteCarloMethodsInFinance](https://github.com/olafSmits/MonteCarloMethodsInFinance) | NEW | 2014-01-21 14:38:39 | 2014-04-21 19:43:21 | 210.0 | :heavy_multiplication_x: | | 108 | | [Data-Science-Essentials](https://github.com/MicrosoftLearning/Data-Science-Essentials) | NEW | 2016-05-16 21:42:29 | 2018-03-01 02:34:46 | 210.0 | :heavy_multiplication_x: | | 109 | | [Python for Finance](https://github.com/siaen/python_finance_course) | CEU python for finance course material. | 2017-12-12 11:54:46 | 2020-02-25 20:31:41 | 21.0 | :heavy_multiplication_x: | | 110 | | [Computational-Social-Science-Training-Program](https://github.com/dlab-berkeley/Computational-Social-Science-Training-Program) | NEW | 2020-07-14 00:53:09 | 2024-09-26 20:27:57 | 209.0 | :heavy_check_mark: | | 111 | | [Machine_Learning_2018](https://github.com/snrazavi/Machine_Learning_2018) | NEW | 2018-10-16 10:16:35 | 2021-09-16 14:14:05 | 208.0 | :heavy_multiplication_x: | | 112 | | [CS-7641-Machine-Learning-Notes](https://github.com/mohamedameen93/CS-7641-Machine-Learning-Notes) | NEW | 2019-01-22 00:53:10 | 2021-01-19 22:18:02 | 203.0 | :heavy_multiplication_x: | | 113 | | [CourseraML](https://github.com/kaleko/CourseraML) | NEW | 2015-12-08 00:03:22 | 2018-10-30 23:49:56 | 2017.0 | :heavy_multiplication_x: | | 114 | | [amazon-sagemaker-architecting-for-ml](https://github.com/aws-samples/amazon-sagemaker-architecting-for-ml) | NEW | 2018-12-20 21:53:20 | 2020-08-12 22:24:32 | 200.0 | :heavy_multiplication_x: | | 115 | | [MLND](https://github.com/mtyylx/MLND) | NEW | 2017-05-07 15:05:10 | 2018-04-01 15:58:24 | 200.0 | :heavy_multiplication_x: | | 116 | | [china-dictatorship](https://github.com/cirosantilli/china-dictatorship) | NEW | 2015-04-02 20:51:50 | 2022-08-03 13:01:21 | 1997.0 | :heavy_multiplication_x: | | 117 | | [cs229-2018-autumn](https://github.com/maxim5/cs229-2018-autumn) | NEW | 2021-02-08 14:39:48 | 2024-04-15 16:56:26 | 1787.0 | :heavy_check_mark: | | 118 | | [Basic Investments](https://github.com/SeanMcOwen/FinanceAndPython.com-Investments) | Basic investment tools in python. | 2017-08-02 21:52:19 | 2017-08-17 03:24:53 | 17.0 | :heavy_multiplication_x: | | 119 | | [DAT8](https://github.com/justmarkham/DAT8) | NEW | 2015-08-07 03:35:51 | 2016-04-18 18:34:09 | 1606.0 | :heavy_multiplication_x: | | 120 | | [ML-YouTube-Courses](https://github.com/dair-ai/ML-YouTube-Courses) | NEW | 2021-06-25 09:39:16 | 2024-01-22 15:52:28 | 15798.0 | :heavy_check_mark: | | 121 | | [PythonNumericalDemos](https://github.com/GeostatsGuy/PythonNumericalDemos) | NEW | 2017-10-13 15:44:06 | 2024-09-10 22:02:32 | 1397.0 | :heavy_check_mark: | | 122 | | [Machine Learning for Trading](https://github.com/stefan-jansen/machine-learning-for-trading) | Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading. | 2018-05-09 12:33:08 | 2023-03-05 17:14:58 | 13043.0 | :heavy_check_mark: | | 123 | | [Basic Finance](https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance) | Source code notebooks basic finance applications. | 2017-05-06 02:39:05 | 2017-06-21 04:04:09 | 13.0 | :heavy_multiplication_x: | | 124 | | [Risk Management](https://github.com/andrey-lukyanov/Risk-Management) | Finance risk engagement course resources. | 2018-10-03 16:26:14 | 2018-12-13 08:04:15 | 13.0 | :heavy_multiplication_x: | | 125 | | [ppd599](https://github.com/gboeing/ppd599) | NEW | 2015-09-01 19:59:59 | 2024-04-28 19:25:58 | 1265.0 | :heavy_check_mark: | | 126 | | [Play-with-Machine-Learning-Algorithms](https://github.com/liuyubobobo/Play-with-Machine-Learning-Algorithms) | NEW | 2017-10-17 23:13:24 | 2022-08-22 00:45:23 | 1259.0 | :heavy_multiplication_x: | | 127 | | [ML_course](https://github.com/epfml/ML_course) | NEW | 2016-07-13 15:37:38 | 2024-09-27 14:37:10 | 1247.0 | :heavy_check_mark: | | 128 | | [home](https://github.com/gege-circle/home) | NEW | 2020-09-20 04:47:25 | 2024-08-15 10:36:10 | 1168.0 | :heavy_check_mark: | | 129 | | [DataCamp](https://github.com/wblakecannon/DataCamp) | NEW | 2017-09-18 20:51:08 | 2020-10-01 20:13:05 | 1167.0 | :heavy_check_mark: | | 130 | | [dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning) | NEW | 2015-02-22 23:48:16 | 2022-06-17 23:22:08 | 11262.0 | :heavy_multiplication_x: | | 131 | | [machine-learning-coursera-1](https://github.com/Borye/machine-learning-coursera-1) | NEW | 2014-08-28 10:48:18 | 2014-06-17 10:37:27 | 1126.0 | :heavy_multiplication_x: | | 132 | | [OptML_course](https://github.com/epfml/OptML_course) | NEW | 2018-02-21 19:06:55 | 2024-06-27 19:57:58 | 1120.0 | :heavy_check_mark: | | 133 | | [Mathematical Finance](https://github.com/yadongli/nyumath2048) | NYU Math-GA 2048: Scientific Computing in Finance. | 2015-01-25 21:10:37 | 2020-03-25 04:24:25 | 106.0 | :heavy_multiplication_x: | | 134 | | [stanford-cs229](https://github.com/zyxue/stanford-cs229) | NEW | 2017-10-31 23:01:08 | 2021-08-04 03:03:28 | 0.0 | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/data_processing_techniques_and_transformations.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:----------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [Advanced ML](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises) | Exercises to book [advances in financial machine learning](https://www.wiley.com/en-us/Advances+in+Financial+Machine+Learning-p-9781119482109). Relevant topics include data cleaning and outlier detection (using MAD) | 2018-04-25 17:22:40 | 2020-01-16 17:25:41 | 1698.0 | :heavy_multiplication_x: | :star:x4 | 4 | | [Twitter-Trends](https://github.com/Medha11/Twitter-Trends) | sentiment analysis baed on twitter data. Relevant topics include data cleaning/tokenization/data aggregation using mangodb etc. | 2017-05-22 17:07:45 | 2017-05-23 08:06:27 | 99.0 | :heavy_multiplication_x: | :star:x3 | 5 | | [Google-Finance-Stock-Data-Analysis](https://github.com/hpnhxxwn/Google-Finance-Stock-Data-Analysis) | data processing platform which stream data from kafka. The example shows two incoming data stream stock vs tweets and two spark streams are created to consume the kafka data then end results are stored in cassandra. Older tech stacks were used and not actively maintained. | 2017-07-23 02:59:59 | 2017-07-23 03:10:35 | 82.0 | :heavy_multiplication_x: | :star:x3 | 6 | | [finserv-application-blueprint](https://github.com/mapr-demos/finserv-application-blueprint) | generate streamable data using mapr converged data platfrom built mostly in java. Uses apache [zepplin](https://zeppelin.apache.org/) for web visualization | 2016-09-26 19:42:54 | 2021-06-07 17:38:13 | 84.0 | :heavy_multiplication_x: | :star:x2 | 7 | | [cointrader](https://github.com/timolson/cointrader) | java based platform for trading crypto. Relevant sections including using esper event queries to transform data and place orders | 2014-06-01 01:14:12 | 2022-06-21 01:03:49 | 451.0 | :heavy_multiplication_x: | :star:x2 | 8 | | [CryptoNets](https://github.com/microsoft/CryptoNets) | CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with [Homomorphic Encryption](https://www.cs.cmu.edu/~odonnell/hits09/gentry-homomorphic-encryption.pdf). Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. | 2019-06-02 05:48:39 | 2022-09-09 15:57:24 | 280.0 | :heavy_multiplication_x: | :star:x2 | 9 | | [plaid-to-gsheets](https://github.com/williamlmao/plaid-to-gsheets) | NEW | 2021-12-12 19:53:14 | 2023-02-03 15:36:49 | 71.0 | :heavy_check_mark: | | 10 | | [ninjabook](https://github.com/ninja-quant/ninjabook) | NEW | 2024-04-10 01:01:10 | 2024-04-21 16:42:28 | 150.0 | :heavy_check_mark: | | 11 | | [Major-project-list](https://github.com/ManojKumarPatnaik/Major-project-list) | NEW | 2021-09-04 11:17:44 | 2024-09-07 15:22:27 | 115.0 | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/derivatives_and_hedging.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:-----------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [Options](https://github.com/PHBS/2018.M1.ASP/tree/master/py) | Black Scholes and Copula. | nan | nan | nan | :heavy_check_mark: | | 4 | | [injective-helix-demo](https://github.com/InjectiveLabs/injective-helix-demo) | NEW | 2021-04-12 13:36:25 | 2024-07-15 17:00:25 | 99.0 | :heavy_check_mark: | | 5 | | [optopsy](https://github.com/michaelchu/optopsy) | NEW | 2017-09-17 01:49:54 | 2024-07-06 19:33:10 | 978.0 | :heavy_check_mark: | | 6 | | [akshare](https://github.com/jindaxiang/akshare) | NEW | 2019-10-01 07:34:12 | 2024-09-28 06:49:57 | 9042.0 | :heavy_check_mark: | | 7 | | [AlgorithmicTrading](https://github.com/JerBouma/AlgorithmicTrading) | NEW | 2019-03-14 09:33:37 | 2023-08-13 07:15:09 | 878.0 | :heavy_check_mark: | | 8 | | [lumibot](https://github.com/Lumiwealth/lumibot) | NEW | 2020-09-10 10:00:16 | 2024-09-27 04:30:14 | 877.0 | :heavy_check_mark: | | 9 | | [Strata](https://github.com/OpenGamma/Strata) | NEW | 2014-06-16 11:45:55 | 2024-08-28 16:12:28 | 842.0 | :heavy_check_mark: | | 10 | | [Derman](https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb) | Binomial tree for American call. | 2018-05-18 18:08:16 | 2018-09-21 19:59:01 | 8.0 | :heavy_multiplication_x: | | 11 | | [Options-Trading-Strategies-in-Python](https://github.com/PyPatel/Options-Trading-Strategies-in-Python) | NEW | 2017-08-30 06:00:15 | 2019-08-21 15:47:57 | 799.0 | :heavy_multiplication_x: | | 12 | | [gs-quant](https://github.com/goldmansachs/gs-quant) | NEW | 2018-12-14 21:10:40 | 2024-09-23 11:01:29 | 7582.0 | :heavy_check_mark: | | 13 | | [StockSharp](https://github.com/StockSharp/StockSharp) | NEW | 2014-12-08 07:53:44 | 2024-09-23 21:13:42 | 7097.0 | :heavy_check_mark: | | 14 | | [optlib](https://github.com/dbrojas/optlib) | NEW | 2020-08-17 00:30:14 | 2022-11-18 19:12:54 | 644.0 | :heavy_check_mark: | | 15 | | [algotrader](https://github.com/torreyleonard/algotrader) | NEW | 2018-04-10 02:31:26 | 2020-08-27 08:16:44 | 635.0 | :heavy_multiplication_x: | | 16 | | [trading-server](https://github.com/s-brez/trading-server) | NEW | 2019-03-05 03:06:19 | 2022-11-17 01:42:13 | 619.0 | :heavy_check_mark: | | 17 | | [Delta Hedging](https://github.com/RobinsonGarcia/delta-hedging) | Advanced derivatives. | 2018-03-02 23:53:53 | 2018-07-17 23:32:23 | 6.0 | :heavy_multiplication_x: | | 18 | | [Option Strategies](https://github.com/rstreppa/valuation-OptionStrategies) | Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations. | 2018-05-22 18:27:26 | 2018-05-22 18:30:24 | 6.0 | :heavy_multiplication_x: | | 19 | | [Derivatives Python](https://github.com/yhilpisch/dawp/tree/master/python36) | Derivative analytics with Python. | 2015-07-09 12:27:29 | 2021-02-22 13:29:18 | 585.0 | :heavy_multiplication_x: | | 20 | | [quant-trading](https://github.com/je-suis-tm/quant-trading) | NEW | 2018-04-03 14:08:14 | 2024-04-14 13:06:59 | 5779.0 | :heavy_check_mark: | | 21 | | [Options](https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D) | Introduction to options. | 2017-07-28 15:48:29 | 2022-06-16 00:35:12 | 525.0 | :heavy_multiplication_x: | | 22 | | [trade-frame](https://github.com/rburkholder/trade-frame) | NEW | 2016-07-24 15:25:30 | 2024-06-16 01:32:50 | 480.0 | :heavy_check_mark: | | 23 | | [Quantsbin](https://github.com/quantsbin/Quantsbin) | NEW | 2018-07-04 02:23:09 | 2021-05-23 18:14:26 | 476.0 | :heavy_multiplication_x: | | 24 | | [tai](https://github.com/fremantle-industries/tai) | NEW | 2017-07-28 03:07:18 | 2022-10-04 03:51:40 | 460.0 | :heavy_check_mark: | | 25 | | [tf-quant-finance](https://github.com/google/tf-quant-finance) | NEW | 2019-07-24 16:09:50 | 2023-08-15 07:37:46 | 4491.0 | :heavy_check_mark: | | 26 | | [QLNet](https://github.com/amaggiulli/QLNet) | NEW | 2013-08-22 14:51:43 | 2024-08-05 15:31:12 | 381.0 | :heavy_check_mark: | | 27 | | [FinanceDatabase](https://github.com/JerBouma/FinanceDatabase) | NEW | 2021-01-28 18:36:09 | 2024-09-22 12:13:59 | 3424.0 | :heavy_check_mark: | | 28 | | [Reinforcement Learning](https://github.com/FinTechies/HedgingRL) | Hedging portfolios with reinforcement learning. | 2017-04-21 10:58:56 | 2017-08-02 21:41:06 | 33.0 | :heavy_multiplication_x: | | 29 | | [Options_Data_Science](https://github.com/yugedata/Options_Data_Science) | NEW | 2020-12-09 04:51:20 | 2022-03-16 19:20:04 | 325.0 | :heavy_multiplication_x: | | 30 | | [Options Risk Measures](https://github.com/wanglouis49/risk_estimation) | Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling). | 2016-04-29 03:51:25 | 2018-01-16 01:24:07 | 3.0 | :heavy_multiplication_x: | | 31 | | [Computational Derivatives](https://github.com/chenbowen184/Computational_Finance) | Projects focusing on investigating simulations and computational techniques applied in finance. | 2018-01-29 05:01:52 | 2018-08-02 05:56:49 | 27.0 | :heavy_multiplication_x: | | 32 | | [investbook](https://github.com/spacious-team/investbook) | NEW | 2020-02-15 18:23:48 | 2024-09-10 12:25:51 | 269.0 | :heavy_check_mark: | | 33 | | [huobi_futures_Python](https://github.com/hbdmapi/huobi_futures_Python) | NEW | 2020-01-14 07:21:39 | 2021-06-25 01:29:01 | 267.0 | :heavy_multiplication_x: | | 34 | | [optionlab](https://github.com/rgaveiga/optionlab) | NEW | 2023-07-04 19:44:27 | 2024-09-13 14:33:35 | 261.0 | :heavy_check_mark: | | 35 | | [paperbroker](https://github.com/philipodonnell/paperbroker) | NEW | 2017-07-06 02:04:51 | 2018-04-08 18:37:57 | 258.0 | :heavy_multiplication_x: | | 36 | | [pancakeswap-prediction-winner](https://github.com/modagavr/pancakeswap-prediction-winner) | NEW | 2021-06-09 14:30:14 | 2023-03-15 06:24:49 | 245.0 | :heavy_check_mark: | | 37 | | [stocktrends](https://github.com/ChillarAnand/stocktrends) | NEW | 2018-02-06 12:56:48 | 2024-04-07 08:31:03 | 240.0 | :heavy_check_mark: | | 38 | | [OptionSuite](https://github.com/sirnfs/OptionSuite) | NEW | 2017-04-13 04:39:44 | 2023-07-10 14:45:36 | 222.0 | :heavy_check_mark: | | 39 | | [bitcoin_volatility_forecasting](https://github.com/chibui191/bitcoin_volatility_forecasting) | NEW | 2021-07-18 17:51:11 | 2021-09-10 20:25:41 | 218.0 | :heavy_multiplication_x: | | 40 | | [FinancePy](https://github.com/domokane/FinancePy) | NEW | 2019-10-27 15:04:56 | 2024-09-09 18:26:26 | 2096.0 | :heavy_check_mark: | | 41 | | [MarketAnalysis](https://github.com/Poseyy/MarketAnalysis) | NEW | 2019-03-28 19:46:34 | 2020-08-06 05:15:46 | 209.0 | :heavy_check_mark: | | 42 | | [MarketAnalysis](https://github.com/p-eq/MarketAnalysis) | NEW | 2019-03-28 19:46:34 | 2020-08-06 05:15:46 | 209.0 | :heavy_check_mark: | | 43 | | [Black Scholes](https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb) | Options pricing. | 2017-12-09 18:50:20 | 2018-07-09 09:48:36 | 2.0 | :heavy_multiplication_x: | | 44 | | [compendium](https://github.com/sambacha/compendium) | NEW | 2019-05-14 01:07:06 | 2023-07-29 13:34:50 | 196.0 | :heavy_check_mark: | | 45 | | [openAlgo](https://github.com/mtompkins/openAlgo) | NEW | 2013-05-28 14:46:53 | 2017-03-24 20:00:24 | 181.0 | :heavy_multiplication_x: | | 46 | | [ibkr-options-volatility-trading](https://github.com/mcf-long-short/ibkr-options-volatility-trading) | NEW | 2021-05-30 12:40:04 | 2021-06-05 13:35:03 | 172.0 | :heavy_multiplication_x: | | 47 | | [robin_stocks](https://github.com/jmfernandes/robin_stocks) | NEW | 2018-02-23 00:49:37 | 2024-07-05 23:16:59 | 1688.0 | :heavy_check_mark: | | 48 | | [option-pricing-models](https://github.com/krivi95/option-pricing-models) | NEW | 2020-11-12 19:00:14 | 2022-01-26 09:40:31 | 164.0 | :heavy_multiplication_x: | | 49 | | [options_backtester](https://github.com/lambdaclass/options_backtester) | NEW | 2019-05-08 14:48:04 | 2024-08-06 22:06:21 | 156.0 | :heavy_check_mark: | | 50 | | [torchquant](https://github.com/jialuechen/torchquant) | NEW | 2022-01-06 04:26:18 | 2024-09-27 03:33:39 | 156.0 | :heavy_check_mark: | | 51 | | [quantlib](https://github.com/piquette/quantlib) | NEW | 2020-04-12 14:20:07 | 2021-04-09 14:53:41 | 142.0 | :heavy_multiplication_x: | | 52 | | [Volatility and Variance Derivatives](https://github.com/yhilpisch/lvvd/tree/master/lvvd) | Volatility derivatives analytics. | 2016-10-21 04:12:50 | 2022-01-04 07:41:22 | 142.0 | :heavy_multiplication_x: | | 53 | | [opstrat](https://github.com/hashABCD/opstrat) | NEW | 2021-03-17 14:31:33 | 2021-07-25 17:16:11 | 141.0 | :heavy_multiplication_x: | | 54 | | [kwenta](https://github.com/Kwenta/kwenta) | NEW | 2021-08-24 16:51:40 | 2023-10-16 19:43:43 | 141.0 | :heavy_check_mark: | | 55 | | [TradingView-Binance-Telegram-Bot](https://github.com/ytrevor81/TradingView-Binance-Telegram-Bot) | NEW | 2021-02-16 07:16:09 | 2022-01-04 13:07:22 | 136.0 | :heavy_multiplication_x: | | 56 | | [fully-automated-nifty-options-trading](https://github.com/srikar-kodakandla/fully-automated-nifty-options-trading) | NEW | 2022-06-25 15:20:23 | 2023-12-23 08:08:20 | 134.0 | :heavy_check_mark: | | 57 | | [wallstreet](https://github.com/mcdallas/wallstreet) | NEW | 2016-01-20 22:03:39 | 2024-03-09 22:31:06 | 1331.0 | :heavy_check_mark: | | 58 | | [fast_arrow](https://github.com/westonplatter/fast_arrow) | NEW | 2018-07-19 23:15:25 | 2020-04-18 18:05:37 | 127.0 | :heavy_multiplication_x: | | 59 | | [10101](https://github.com/get10101/10101) | NEW | 2023-01-11 04:46:13 | 2024-08-10 11:55:40 | 127.0 | :heavy_check_mark: | | 60 | | [tda-api](https://github.com/alexgolec/tda-api) | NEW | 2020-04-03 21:19:12 | 2024-06-16 22:04:19 | 1265.0 | :heavy_check_mark: | | 61 | | [harvest](https://github.com/tfukaza/harvest) | NEW | 2021-06-25 21:29:38 | 2024-06-04 21:02:57 | 122.0 | :heavy_check_mark: | | 62 | | [renegade-way](https://github.com/evdubs/renegade-way) | NEW | 2019-08-24 00:42:24 | 2024-08-24 01:06:42 | 121.0 | :heavy_check_mark: | | 63 | | [Hull White](https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb) | Callable Bond, Hull White. | 2018-06-06 22:06:06 | 2018-06-06 22:27:02 | 12.0 | :heavy_multiplication_x: | | 64 | | [Iq_Option_Bots](https://github.com/metheuspsc/Iq_Option_Bots) | NEW | 2020-06-22 12:35:22 | 2021-08-18 01:31:21 | 119.0 | :heavy_multiplication_x: | | 65 | | [python-option-calculator](https://github.com/yzoz/python-option-calculator) | NEW | 2017-02-07 15:46:31 | 2022-09-13 16:20:00 | 118.0 | :heavy_multiplication_x: | | 66 | | [betterOptionsTrading](https://github.com/amit0rana/betterOptionsTrading) | NEW | 2020-04-08 10:34:52 | 2024-09-23 04:57:39 | 117.0 | :heavy_check_mark: | | 67 | | [FlowAlgo-Options-Trader](https://github.com/SC4RECOIN/FlowAlgo-Options-Trader) | NEW | 2020-11-12 03:05:58 | 2021-02-15 19:28:42 | 115.0 | :heavy_multiplication_x: | | 68 | | [LoopTrader](https://github.com/pattertj/LoopTrader) | NEW | 2021-04-04 16:47:20 | 2022-03-28 15:17:16 | 114.0 | :heavy_multiplication_x: | | 69 | | [pyBlackScholesAnalytics](https://github.com/gabrielepompa88/pyBlackScholesAnalytics) | NEW | 2020-08-11 14:18:39 | 2020-09-02 10:27:27 | 111.0 | :heavy_multiplication_x: | | 70 | | [Derivative Markets](https://github.com/broughtj/Fin6470/tree/master/Notebooks) | The economics of futures, futures, options, and swaps. | 2016-02-09 05:30:27 | 2021-04-15 16:02:59 | 11.0 | :heavy_multiplication_x: | | 71 | | [binance-copy-trade-bot](https://github.com/tpmmthomas/binance-copy-trade-bot) | NEW | 2022-06-23 08:08:00 | 2024-06-20 20:41:33 | 109.0 | :heavy_check_mark: | | 72 | | [RustQuant](https://github.com/avhz/RustQuant) | NEW | 2022-08-31 10:03:24 | 2024-09-05 20:15:03 | 1067.0 | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/factor_and_risk_analysis.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [-1](https://github.com/Rastaman4e/-1) | NEW | nan | nan | nan | :heavy_check_mark: | | 4 | | [FEEDN](https://github.com/THEFEASTCOIN/FEEDN) | NEW | nan | nan | nan | :heavy_check_mark: | | 5 | | [factor-risk-parity](https://github.com/tngaspar/factor-risk-parity) | NEW | 2020-04-05 17:05:40 | 2022-09-18 14:42:03 | 9.0 | :heavy_multiplication_x: | | 6 | | [SafetyAndTrade](https://github.com/vrdcas/SafetyAndTrade) | NEW | 2020-04-11 20:18:03 | 2020-04-12 17:00:36 | 9.0 | :heavy_multiplication_x: | | 7 | | [VaR GaN](https://github.com/hamaadshah/market_risk_gan_keras) | Estimate Value-at-Risk for market risk management using Keras and TensorFlow. | 2018-08-06 16:09:44 | 2022-06-24 19:05:55 | 84.0 | :heavy_multiplication_x: | | 8 | | [Liberty-House-Club-Whitepaper](https://github.com/realbeeed/Liberty-House-Club-Whitepaper) | NEW | 2022-04-22 08:25:39 | 2022-04-22 08:27:24 | 8.0 | :heavy_check_mark: | | 9 | | [Various Risk Measures](https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb) | Risk measures and factors for alternative and responsible investments. | 2017-08-07 14:44:32 | 2017-08-08 22:52:11 | 8.0 | :heavy_multiplication_x: | | 10 | | [Factor Analysis](https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb) | Factor analysis for mutual funds. | 2018-03-13 07:39:20 | 2018-03-13 07:42:36 | 8.0 | :heavy_multiplication_x: | | 11 | | [one_factor_Hull_White_python](https://github.com/open-source-modelling/one_factor_Hull_White_python) | NEW | 2023-01-29 17:45:51 | 2024-03-24 19:48:04 | 8.0 | :heavy_check_mark: | | 12 | | [whitepaper](https://github.com/peacockbsc/whitepaper) | NEW | 2021-07-31 23:39:41 | 2022-08-25 09:52:38 | 7.0 | :heavy_multiplication_x: | | 13 | | [An-Analysis-of-PCA-and-Autoencoder-Generated-Factors-in-Predicting-SP500-Returns](https://github.com/Leo8216/An-Analysis-of-PCA-and-Autoencoder-Generated-Factors-in-Predicting-SP500-Returns) | NEW | 2020-01-18 00:53:46 | 2020-01-18 03:59:36 | 7.0 | :heavy_multiplication_x: | | 14 | | [The-Reason-Why-Everyone-Love-Mining-Tools](https://github.com/dcstechnoweb/The-Reason-Why-Everyone-Love-Mining-Tools) | NEW | 2022-06-13 05:11:36 | 2022-06-13 05:12:52 | 7.0 | :heavy_multiplication_x: | | 15 | | [-L-](https://github.com/jettbrains/-L-) | NEW | 2019-10-28 21:50:26 | 2019-10-28 21:51:19 | 67.0 | :heavy_multiplication_x: | | 16 | | [Bitcoin_Since_Pandemic](https://github.com/at-tan/Bitcoin_Since_Pandemic) | NEW | 2022-02-12 11:12:37 | 2022-02-12 17:46:45 | 6.0 | :heavy_multiplication_x: | | 17 | | [Pyfolio](https://github.com/quantopian/pyfolio) | Portfolio and risk analytics in Python. | 2015-06-01 15:31:39 | 2020-02-28 17:30:19 | 5631.0 | :heavy_multiplication_x: | | 18 | | [financeMacroFactors](https://github.com/sankhaMukherjee/financeMacroFactors) | NEW | 2020-07-22 15:42:14 | 2020-08-23 14:17:13 | 5.0 | :heavy_multiplication_x: | | 19 | | [Quant Finance](https://github.com/mrefermat/quant_finance) | General quant repository. | 2018-08-11 22:59:53 | 2019-11-12 04:49:01 | 47.0 | :heavy_multiplication_x: | | 20 | | [CAPM](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb) | Expected returns using CAPM. | 2016-05-10 11:03:48 | 2016-05-17 03:44:56 | 44.0 | :heavy_multiplication_x: | | 21 | | [Risk Basic](https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb) | Active portfolio risk management . | 2016-05-10 11:03:48 | 2016-05-17 03:44:56 | 44.0 | :heavy_multiplication_x: | | 22 | | [Long-Term-Stock-Price-Growth-Prediction-using-NLP-on-10-K-Financial-Reports](https://github.com/deepak223098/Long-Term-Stock-Price-Growth-Prediction-using-NLP-on-10-K-Financial-Reports) | NEW | 2019-12-21 07:14:30 | 2020-07-06 11:21:13 | 40.0 | :heavy_multiplication_x: | | 23 | | [toraniko](https://github.com/0xfdf/toraniko) | NEW | 2024-07-03 04:04:59 | 2024-08-05 04:58:20 | 376.0 | :heavy_check_mark: | | 24 | | [Empirical-Method-in-Finance](https://github.com/yitaohu88/Empirical-Method-in-Finance) | NEW | 2021-01-13 23:48:30 | 2021-01-13 23:57:32 | 34.0 | :heavy_multiplication_x: | | 25 | | [Statistical Finance](https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments) | Various financial experiments. | 2015-10-04 09:10:54 | 2020-03-28 18:33:58 | 33.0 | :heavy_multiplication_x: | | 26 | | [Performance Analysis](https://github.com/quantopian/alphalens) | Performance analysis of predictive (alpha) stock factors. | 2016-06-03 21:49:15 | 2020-04-27 18:40:41 | 3282.0 | :heavy_multiplication_x: | | 27 | | [AlphaTrading](https://github.com/jerryxyx/AlphaTrading) | NEW | 2018-05-18 22:09:52 | 2018-08-07 18:05:37 | 324.0 | :heavy_multiplication_x: | | 28 | | [equity-risk-model](https://github.com/blaahhrrgg/equity-risk-model) | NEW | 2021-11-16 11:29:57 | 2024-01-30 11:48:44 | 31.0 | :heavy_check_mark: | | 29 | | [Convex Optimisation](https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb) | Convex Optimization for Finance. | 2018-06-26 20:36:47 | 2019-10-22 21:56:46 | 28.0 | :heavy_multiplication_x: | | 30 | | [Factor Analysis](https://github.com/alpha-miner/alpha-mind/tree/master/notebooks) | Factor strategy notebooks. | 2017-05-01 07:36:54 | 2022-05-21 15:02:13 | 226.0 | :heavy_multiplication_x: | | 31 | | [stock-market-analysis-using-python-numpy-pandas](https://github.com/Ashishsinha10/stock-market-analysis-using-python-numpy-pandas) | NEW | 2018-04-10 05:15:49 | 2018-04-10 05:28:54 | 21.0 | :heavy_multiplication_x: | | 32 | | [Stock-Prediction](https://github.com/Ronak-59/Stock-Prediction) | NEW | 2018-03-18 04:54:45 | 2020-02-28 11:43:07 | 207.0 | :heavy_multiplication_x: | | 33 | | [Machine_learning_In_Finance](https://github.com/chaudharigauravi/Machine_learning_In_Finance) | NEW | 2019-08-03 04:04:51 | 2019-08-03 04:05:32 | 18.0 | :heavy_multiplication_x: | | 34 | | [Python for Finance](https://github.com/yhilpisch/py4fi/tree/master/jupyter36) | Various financial notebooks. | 2014-12-15 11:23:34 | 2018-07-10 06:38:12 | 1794.0 | :heavy_multiplication_x: | | 35 | | [Risk and Return](https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials) | Riskiness of portfolios and assets. | 2017-09-12 13:35:09 | 2020-08-06 12:35:44 | 168.0 | :heavy_multiplication_x: | | 36 | | [simulate](https://github.com/leolle/simulate) | NEW | 2017-06-04 15:18:21 | 2018-11-11 14:03:40 | 16.0 | :heavy_multiplication_x: | | 37 | | [Bitcoin-Price-Prediction-using-AI-ML.](https://github.com/ananya2001gupta/Bitcoin-Price-Prediction-using-AI-ML.) | NEW | 2022-08-02 13:16:50 | 2022-08-02 14:29:16 | 15.0 | :heavy_multiplication_x: | | 38 | | [Liberty-House-Club-Whitepaper](https://github.com/Mdshobu/Liberty-House-Club-Whitepaper) | NEW | 2022-07-12 18:36:00 | 2022-04-22 08:27:24 | 15.0 | :heavy_multiplication_x: | | 39 | | [Quantitative-Trading-Strategy-Based-on-Machine-Learning](https://github.com/majiajue/Quantitative-Trading-Strategy-Based-on-Machine-Learning) | NEW | 2020-08-07 06:22:35 | 2020-08-04 06:20:36 | 14.0 | :heavy_multiplication_x: | | 40 | | [Quantropy](https://github.com/AlainDaccache/Quantropy) | NEW | 2020-06-13 15:34:25 | 2021-03-15 01:49:23 | 135.0 | :heavy_multiplication_x: | | 41 | | [TradeFinexLive](https://github.com/XinFinOrg/TradeFinexLive) | NEW | 2018-03-21 10:05:22 | 2021-08-16 11:40:03 | 13.0 | :heavy_multiplication_x: | | 42 | | [VaR](https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb) | Value-at-risk calculations. | 2016-11-15 19:24:17 | 2017-01-14 21:19:30 | 11.0 | :heavy_multiplication_x: | | -------------------------------------------------------------------------------- /generated_wiki/fixed_income.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:-----------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [Binomial Tree](https://github.com/hy-lei/math-finance-exercise) | Utility functions in fixed income securities. | 2019-02-02 08:44:14 | 2019-05-03 17:16:52 | 8.0 | :heavy_multiplication_x: | | 4 | | [Vasicek](https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb) | Bootstrapping and interpolation. | 2018-07-18 19:26:54 | 2018-07-18 19:34:48 | 6.0 | :heavy_multiplication_x: | | 5 | | [neurons](https://github.com/Aryia-Behroziuan/neurons) | NEW | 2020-11-07 12:17:04 | 2020-11-07 12:17:06 | 55.0 | :heavy_multiplication_x: | | 6 | | [R-fixedincome](https://github.com/wilsonfreitas/R-fixedincome) | NEW | 2013-09-16 01:10:50 | 2023-06-27 08:10:20 | 51.0 | :heavy_check_mark: | | 7 | | [rating_history](https://github.com/govwiki/rating_history) | NEW | 2017-11-23 22:52:14 | 2023-06-29 22:16:57 | 47.0 | :heavy_check_mark: | | 8 | | [TRACE-corporate-bond-processing](https://github.com/Alexander-M-Dickerson/TRACE-corporate-bond-processing) | NEW | 2020-12-18 10:20:12 | 2024-07-18 02:33:32 | 43.0 | :heavy_check_mark: | | 9 | | [augmented-finance-protocol](https://github.com/augmented-finance/augmented-finance-protocol) | NEW | 2021-03-27 11:01:43 | 2022-02-16 15:58:35 | 38.0 | :heavy_multiplication_x: | | 10 | | [market-data](https://github.com/kriasoft/market-data) | NEW | 2012-12-07 13:42:48 | 2012-12-15 12:10:06 | 35.0 | :heavy_multiplication_x: | | 11 | | [DROP-Fixed-Income](https://github.com/lakshmiDRIP/DROP-Fixed-Income) | NEW | 2017-08-10 20:58:18 | 2018-09-26 19:21:02 | 28.0 | :heavy_multiplication_x: | | 12 | | [woe](https://github.com/boredbird/woe) | NEW | 2017-09-11 07:15:04 | 2018-03-01 10:45:40 | 256.0 | :heavy_multiplication_x: | | 13 | | [punk.protocol](https://github.com/PunkFinance/punk.protocol) | NEW | 2021-04-29 08:39:42 | 2021-08-13 11:53:11 | 23.0 | :heavy_multiplication_x: | | 14 | | [fixed-income](https://github.com/daniel-m-campos/fixed-income) | NEW | 2017-09-17 05:23:47 | 2020-12-18 01:35:41 | 21.0 | :heavy_multiplication_x: | | 15 | | [sagemaker-corporate-credit-rating](https://github.com/awslabs/sagemaker-corporate-credit-rating) | NEW | 2021-11-12 00:49:14 | 2022-12-20 17:11:03 | 20.0 | :heavy_check_mark: | | 16 | | [Corporate Bonds](https://github.com/ishank011/gs-quantify-bond-prediction) | Predicting the buying and selling volume of the corporate bonds. | 2017-09-27 19:57:13 | 2017-09-27 20:00:29 | 19.0 | :heavy_multiplication_x: | | 17 | | [pyratings](https://github.com/hsbc/pyratings) | NEW | 2022-03-24 14:51:59 | 2024-06-18 07:03:07 | 19.0 | :heavy_check_mark: | | 18 | | [rateslib](https://github.com/attack68/rateslib) | NEW | 2023-03-31 12:47:27 | 2024-09-25 16:07:35 | 128.0 | :heavy_check_mark: | | 19 | | [MagentoExtensions](https://github.com/5mehulhelp5/MagentoExtensions) | NEW | 2014-07-03 05:45:54 | 2024-07-29 08:14:55 | 121.0 | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/personal_papers.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:--------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------|:------------------------|:-------------------------|:------------------------|:------------------------------|:--------------------| 3 | | [Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization](https://jfds.pm-research.com/content/2/2/17) | nan | nan | nan | nan | :heavy_check_mark: | | 4 | | [Machine Learning in Asset Management](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420952) | nan | nan | nan | nan | :heavy_check_mark: | | 5 | | [Financial Event Prediction using Machine Learning](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3481555) | nan | nan | nan | nan | :heavy_check_mark: | | 6 | | [Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies](https://jfds.pm-research.com/content/2/1/10) | nan | nan | nan | nan | :heavy_check_mark: | | -------------------------------------------------------------------------------- /generated_wiki/portfolio_selection_and_optimisation.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:--------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [Modern Portfolio Theory](https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb) | Universal portfolios; modern portfolio theory. | nan | nan | nan | :heavy_check_mark: | | 4 | | [Online Portfolio Selection](https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb) | ****Comparing OLPS algorithms on a diversified set of ETFs. | nan | nan | nan | :heavy_check_mark: | | 5 | | [cvxportfolio](https://github.com/cvxgrp/cvxportfolio) | NEW | 2017-01-11 01:16:16 | 2024-09-27 14:09:43 | 968.0 | :heavy_check_mark: | | 6 | | [DeepDow](https://github.com/jankrepl/deepdow) | Portfolio optimization with deep learning. | 2020-02-02 08:46:33 | 2024-01-24 15:56:34 | 901.0 | :heavy_check_mark: | | 7 | | [Reinforcement Learning](https://github.com/filangel/qtrader) | Reinforcement Learning for Portfolio Management. | 2017-10-07 09:14:33 | 2018-06-26 09:22:27 | 453.0 | :heavy_multiplication_x: | | 8 | | [PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt) | Financial portfolio optimisation, including classical efficient frontier and advanced methods. | 2018-05-29 13:30:30 | 2024-05-28 23:05:51 | 4425.0 | :heavy_check_mark: | | 9 | | [Distribution Characteristic Optimisation](https://github.com/VivekPa/OptimalPortfolio) | Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account. | 2018-11-16 12:20:25 | 2024-02-27 21:38:36 | 352.0 | :heavy_check_mark: | | 10 | | [Riskfolio-Lib](https://github.com/dcajasn/Riskfolio-Lib) | NEW | 2020-03-02 19:49:06 | 2024-07-29 21:51:42 | 2985.0 | :heavy_check_mark: | | 11 | | [riskparity.py](https://github.com/convexfi/riskparity.py) | NEW | 2019-07-13 21:30:55 | 2024-05-27 00:29:29 | 285.0 | :heavy_check_mark: | | 12 | | [riskparity.py](https://github.com/dppalomar/riskparity.py) | NEW | 2019-07-13 21:30:55 | 2024-05-27 00:29:29 | 285.0 | :heavy_check_mark: | | 13 | | [okama](https://github.com/mbk-dev/okama) | NEW | 2020-03-02 14:48:29 | 2024-07-06 13:39:25 | 205.0 | :heavy_check_mark: | | 14 | | [Efficient Frontier](https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb) | Modern Portfolio Theory. | 2018-02-17 08:19:46 | 2018-02-27 13:16:57 | 184.0 | :heavy_multiplication_x: | | 15 | | [Policy Gradient Portfolio](https://github.com/ZhengyaoJiang/PGPortfolio) | A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem. | 2017-11-12 16:08:44 | 2021-07-30 15:03:59 | 1739.0 | :heavy_multiplication_x: | | 16 | | [finance-courses](https://github.com/z4ir3/finance-courses) | NEW | 2019-10-10 10:50:03 | 2023-12-11 23:09:10 | 171.0 | :heavy_check_mark: | | 17 | | [401K Portfolio Optimisation](https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb) | Portfolio analyses and optimisation for 401K. | 2018-08-01 19:48:24 | 2019-09-05 11:18:56 | 17.0 | :heavy_multiplication_x: | | 18 | | [Deep Portfolio Theory](https://github.com/tcloaa/Deep-Portfolio-Theory) | Autoencoder framework for portfolio selection. | 2017-02-10 09:03:08 | 2018-03-08 16:47:00 | 129.0 | :heavy_multiplication_x: | | 19 | | [node-finance](https://github.com/albertosantini/node-finance) | NEW | 2011-09-17 17:49:56 | 2022-09-30 05:08:24 | 122.0 | :heavy_check_mark: | | 20 | | [portfolio-optimize](https://github.com/manujajay/portfolio-optimize) | NEW | 2024-03-10 19:40:41 | 2024-03-11 23:33:22 | 112.0 | :heavy_check_mark: | | 21 | | [OLMAR Algorithm](https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb) | Relative importance of each component of the OLMAR algorithm. | 2016-07-26 16:20:10 | 2016-12-30 11:40:53 | 11.0 | :heavy_multiplication_x: | | -------------------------------------------------------------------------------- /generated_wiki/reinforcement_learning.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------|:-------------------------|:-------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [RL Trading](https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW) | A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab. | nan | nan | nan | :heavy_check_mark: | | 4 | | [RL](https://github.com/kh-kim/stock_market_reinforcement_learning) | OpenGym with Deep Q-learning and Policy Gradient. | 10/4/16 14:42 | 12/23/16 7:34 | 713.0 | :heavy_multiplication_x: | | 5 | | [RL III](https://github.com/samre12/deep-trading-agent) | Github -Deep Reinforcement Learning based Trading Agent for Bitcoin. | 9/21/17 17:05 | 4/13/18 16:33 | 576.0 | :heavy_multiplication_x: | | 6 | | [RL V](https://github.com/gstenger98/rl-finance) | Building an Agent to Trade with Reinforcement Learning. | 1/16/19 0:43 | 3/19/20 20:28 | 32.0 | :heavy_check_mark: | | 7 | | [Pair Trading RL](https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading) | Using deep actor-critic model to learn best strategies in pair trading. | 5/18/17 16:47 | 5/18/17 16:56 | 241.0 | :heavy_multiplication_x: | | 8 | | [RL IV](https://github.com/jjakimoto/DQN) | Reinforcement Learning for finance. | 10/21/16 2:47 | 4/7/17 8:11 | 140.0 | :heavy_multiplication_x: | | 9 | | [RL II](https://github.com/deependersingla/deep_trader) | reinforcement learning on stock market and agent tries to learn trading. | 6/11/16 7:27 | 1/22/18 14:35 | 1340.0 | :heavy_multiplication_x: | | -------------------------------------------------------------------------------- /generated_wiki/textual.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [NLP](https://github.com/toamitesh/NLPinFinance) | This project assembles a lot of NLP operations needed for finance domain. | nan | nan | nan | :heavy_check_mark: | | 4 | | [NLP Event](https://github.com/yuriak/DLQuant) | Applying Deep Learning and NLP in Quantitative Trading. | 2018-07-02 23:50:52 | 2019-01-31 14:08:20 | 99.0 | :heavy_multiplication_x: | | 5 | | [Financial Sentiment Analysis](https://github.com/EricHe98/Financial-Statements-Text-Analysis) | Sentiment, distance and proportion analysis for trading signals. | 2017-06-23 00:05:49 | 2023-05-08 00:58:50 | 94.0 | :heavy_check_mark: | | 6 | | [Cornucopia-LLaMA-Fin-Chinese](https://github.com/jerry1993-tech/Cornucopia-LLaMA-Fin-Chinese) | NEW | 2023-04-30 06:11:18 | 2023-06-30 07:52:13 | 582.0 | :heavy_check_mark: | | 7 | | [awesome-financial-nlp](https://github.com/icoxfog417/awesome-financial-nlp) | NEW | 2019-10-03 03:53:20 | 2020-02-01 08:28:16 | 402.0 | :heavy_multiplication_x: | | 8 | | [Buzzwords](https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds) | Return performance and mutual fund selection. | 2018-02-04 21:51:16 | 2018-02-04 21:57:09 | 4.0 | :heavy_multiplication_x: | | 9 | | [FinNLP-Progress](https://github.com/YangLinyi/FinNLP-Progress) | NEW | 2020-05-21 09:59:56 | 2022-04-18 09:21:22 | 390.0 | :heavy_multiplication_x: | | 10 | | [news-emotion](https://github.com/dongyuanxin/news-emotion) | NEW | 2017-09-14 02:59:03 | 2018-06-11 13:47:51 | 331.0 | :heavy_multiplication_x: | | 11 | | [financial-news-dataset](https://github.com/philipperemy/financial-news-dataset) | NEW | 2016-08-23 13:29:07 | 2023-03-09 06:53:26 | 223.0 | :heavy_check_mark: | | 12 | | [FinBERT](https://github.com/psnonis/FinBERT) | NEW | 2019-07-09 16:34:27 | 2020-05-19 02:02:20 | 197.0 | :heavy_multiplication_x: | | 13 | | [Accounting Anomalies](https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb) | Using deep-learning frameworks to identify accounting anomalies. | 2017-05-24 12:36:38 | 2019-08-07 21:47:08 | 196.0 | :heavy_multiplication_x: | | 14 | | [fin-sight](https://github.com/vishwasg217/fin-sight) | NEW | 2023-09-06 13:01:39 | 2024-04-22 07:21:27 | 195.0 | :heavy_check_mark: | | 15 | | [finsight](https://github.com/vishwasg217/finsight) | NEW | 2023-09-06 13:01:39 | 2024-04-22 07:21:27 | 189.0 | :heavy_check_mark: | | 16 | | [Financial Statement Sentiment](https://github.com/MAydogdu/TextualAnalysis) | Extracting sentiment from financial statements using neural networks. | 2018-06-04 20:54:14 | 2018-06-04 20:56:02 | 18.0 | :heavy_multiplication_x: | | 17 | | [BDCI2019-Negative_Finance_Info_Judge](https://github.com/A-Rain/BDCI2019-Negative_Finance_Info_Judge) | NEW | 2019-12-27 03:49:31 | 2020-12-04 03:38:57 | 153.0 | :heavy_multiplication_x: | | 18 | | [ChatGPT-for-FinTech](https://github.com/AI4Finance-Foundation/ChatGPT-for-FinTech) | NEW | 2023-02-11 20:21:34 | 2024-07-18 06:34:35 | 13611.0 | :heavy_check_mark: | | 19 | | [Extensive NLP](https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb) | Comprehensive NLP techniques for accounting research. | 2017-10-25 07:10:26 | 2020-06-05 03:28:46 | 118.0 | :heavy_multiplication_x: | | 20 | | [Fund classification](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb) | Fund classification using text mining and NLP. | 2018-04-16 22:18:55 | 2018-06-07 22:01:32 | 11.0 | :heavy_multiplication_x: | | 21 | | [Earning call transcripts](https://github.com/lin882/WebAnalyticsProject) | Correlation between mutual fund investment decision and earning call transcripts. | 2017-12-30 08:56:03 | 2018-01-11 02:11:11 | 10.0 | :heavy_multiplication_x: | | -------------------------------------------------------------------------------- /generated_wiki/unsupervised.md: -------------------------------------------------------------------------------- 1 | | repo | comment | created_at | last_commit | star_count | repo_status | rating | 2 | |:-------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------|:-------------------------------|:-------------------------------|:------------------------|:------------------------------------|:--------------------| 3 | | [PCA Pairs Trading](https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading) | PCA, Factor Returns, and trading strategies. | nan | nan | nan | :heavy_check_mark: | | 4 | | [Eigen-Portfolio](https://github.com/Gustrigos/Eigen-Portfolio) | NEW | 2018-09-05 05:29:18 | 2020-04-09 21:40:04 | 67.0 | :heavy_multiplication_x: | | 5 | | [hmm_market_behavior](https://github.com/lamres/hmm_market_behavior) | NEW | 2019-09-08 17:37:39 | 2020-05-10 14:36:03 | 40.0 | :heavy_multiplication_x: | | 6 | | [VRA Stock Embedding](https://github.com/ml-hongkong/stock2vec) | Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history. | 2017-06-21 04:47:14 | 2017-06-21 04:51:13 | 38.0 | :heavy_multiplication_x: | | 7 | | [AnomalyDetectionOnRisk](https://github.com/SimonWesterlindVPD/AnomalyDetectionOnRisk) | NEW | 2018-05-31 15:53:02 | 2018-05-31 16:18:28 | 21.0 | :heavy_multiplication_x: | | 8 | | [Pairs Trading](https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb) | Finding pairs with cluster analysis. | 2017-09-05 19:19:19 | 2017-09-27 20:42:14 | 203.0 | :heavy_multiplication_x: | | 9 | | [all-classification-templetes-for-ML](https://github.com/sayantann11/all-classification-templetes-for-ML) | NEW | 2020-05-05 10:28:52 | 2024-05-15 11:46:23 | 198.0 | :heavy_check_mark: | | 10 | | [Credit-Card-Fraud-Detection](https://github.com/sharmaroshan/Credit-Card-Fraud-Detection) | NEW | 2019-03-31 05:33:17 | 2019-03-31 05:38:43 | 16.0 | :heavy_multiplication_x: | | 11 | | [Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries) | Clustering of industries. | 2017-07-21 02:12:51 | 2017-07-23 02:53:37 | 14.0 | :heavy_multiplication_x: | | 12 | | [Industry Clustering](https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries) | Project to cluster industries according to financial attributes. | 2017-07-21 02:12:51 | 2017-07-23 02:53:37 | 14.0 | :heavy_multiplication_x: | | 13 | | [tableQA-Chinese](https://github.com/svjack/tableQA-Chinese) | NEW | 2021-03-16 14:54:53 | 2023-04-20 06:20:56 | 12.0 | :heavy_check_mark: | | 14 | | [Fund Clusters](https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb) | Data exploration of fund clusters. | 2018-04-16 22:18:55 | 2018-06-07 22:01:32 | 11.0 | :heavy_multiplication_x: | | 15 | | [Stock_Support_Resistance_ML](https://github.com/judopro/Stock_Support_Resistance_ML) | NEW | 2019-12-22 20:25:48 | 2021-05-02 04:25:21 | 100.0 | :heavy_multiplication_x: | | 16 | | [Learning-Technical-Trading](https://github.com/NJ-Murphy/Learning-Technical-Trading) | NEW | 2019-03-25 11:47:49 | 2020-04-08 12:39:53 | 10.0 | :heavy_multiplication_x: | | -------------------------------------------------------------------------------- /git_search.py: -------------------------------------------------------------------------------- 1 | import datetime 2 | import os 3 | from typing import Dict, List 4 | 5 | import pandas as pd 6 | 7 | from conf import PROJECT_ROOT_DIR 8 | from git_status import get_repo_list 9 | from git_util import get_github_client, get_repo_attributes_dict 10 | 11 | 12 | def convert_repo_list_to_df(repo_list, category): 13 | df_list = [] 14 | for repo in repo_list: 15 | print(repo) 16 | attr_dict = get_repo_attributes_dict(repo) 17 | attr_dict['name'] = repo.name 18 | attr_dict['comment'] = 'NEW' 19 | attr_dict['category'] = category 20 | attr_dict['repo_path'] = repo.full_name 21 | attr_dict['url'] = 'https://github.com/{}'.format(repo.full_name) 22 | df_list.append(attr_dict) 23 | result_df = pd.DataFrame(df_list) 24 | return result_df 25 | 26 | 27 | # generic search functions 28 | def search_repo(search_term: str, qualifier_dict: Dict): 29 | g = get_github_client() 30 | qualifier_str = ' '.join(['{}:{}'.format(k, v) for k, v in iter(qualifier_dict.items())]) 31 | if qualifier_str != '': 32 | final_search_term = '{} {}'.format(search_term, qualifier_str) 33 | else: 34 | final_search_term = search_term 35 | repo_result = g.search_repositories(final_search_term) 36 | return repo_result 37 | 38 | 39 | def search_repo_multiple_terms(term_list: List[str], 40 | category: str, 41 | min_stars_number: int = None, 42 | created_at: str = None, 43 | pushed_date: str = None, 44 | drop_duplicate: bool = True 45 | ): 46 | """ 47 | 48 | :param term_list: 49 | :param category: 50 | :param min_stars_number: 51 | :param created_at: 52 | :param pushed_date: 53 | :param drop_duplicate: 54 | :return: 55 | usage: 56 | >>> term_list = ['deep learning trading', 'deep learning finance', 'reinforcement learning trading', 57 | 'reinforcement learning finance'] 58 | >>> category = 'Deep Learning And Reinforcement Learning' 59 | >>> min_stars_number = 100 60 | >>> created_at = None 61 | >>> pushed_date = None 62 | >>> drop_duplicate = True 63 | """ 64 | repo_df_list = [] 65 | for search_term in term_list: 66 | repo_list = search_repo_simple(search_term, min_stars_number, created_at=created_at, pushed_date=pushed_date) 67 | repo_df = convert_repo_list_to_df(repo_list, category) 68 | repo_df_list.append(repo_df) 69 | combined_df = pd.concat(repo_df_list).reset_index(drop=True) 70 | if drop_duplicate: 71 | combined_df = combined_df.drop_duplicates() 72 | combined_df['finml_added_date'] = datetime.datetime.now() 73 | return combined_df 74 | 75 | 76 | def search_repo_simple(search_term: str = None, 77 | min_stars_number: int = None, 78 | created_at: str = None, 79 | pushed_date: str = None 80 | ): 81 | """ 82 | 83 | :param search_term: 84 | :param min_stars_number: 85 | :param created_at: 86 | :param pushed_date: 87 | usage: 88 | >>> search_term = 'machine learning trading' 89 | >>> min_stars_number = 100 90 | >>> created_at = None 91 | >>> pushed_date = None 92 | """ 93 | if search_term is None: 94 | _search_term = '' 95 | else: 96 | _search_term = search_term 97 | 98 | qualifier_dict = {} 99 | if min_stars_number is not None: 100 | qualifier_dict['stars'] = '>={}'.format(min_stars_number) 101 | 102 | if created_at is not None: 103 | qualifier_dict['created'] = '>={}'.format(created_at) 104 | 105 | if pushed_date is not None: 106 | qualifier_dict['pushed'] = '>={}'.format(pushed_date) 107 | search_result = search_repo(_search_term, qualifier_dict) 108 | return search_result 109 | 110 | 111 | def search_new_repo_by_category(category: str, 112 | min_stars_number: int = 100, 113 | existing_repo_df: pd.DataFrame = None): 114 | """ 115 | 116 | :param category: 117 | :param min_stars_number: 118 | :param existing_repo_df: 119 | :return: 120 | usage: 121 | >>> category = 'Data Processing Techniques and Transformations' 122 | >>> min_stars_number = 100 123 | >>> existing_repo_df = get_repo_list() 124 | """ 125 | print('*** searching for category [{}] ***'.format(category)) 126 | combined_df = None 127 | if category == 'Deep Learning And Reinforcement Learning': 128 | combined_df = search_repo_multiple_terms(['deep learning trading', 129 | 'deep learning finance', 130 | 'reinforcement learning trading', 131 | 'reinforcement learning finance'], 132 | category, 133 | min_stars_number=min_stars_number 134 | ) 135 | 136 | elif category == 'Other Models': 137 | combined_df = search_repo_multiple_terms(['machine learning trading', 138 | 'machine learning finance'], 139 | category, 140 | min_stars_number=min_stars_number 141 | ) 142 | elif category == 'Data Processing Techniques and Transformations': 143 | combined_df = search_repo_multiple_terms(['data transformation trading', 144 | 'data transformation finance', 145 | 'data transformation time series', 146 | 'data processing trading', 147 | 'data processing finance', 148 | 'power transform trading', 149 | 'power transform finance', 150 | 'standardization normalization trading', 151 | 'standardization normalization finance', 152 | ], 153 | category, 154 | min_stars_number=int(min_stars_number * 0.5) 155 | ) 156 | elif category == 'Portfolio Selection and Optimisation': 157 | combined_df = search_repo_multiple_terms(['portfolio optimization machine learning finance', 158 | 'portfolio optimization machine learning trading', 159 | 'portfolio construction machine learning finance', 160 | 'portfolio construction machine learning trading', 161 | 'portfolio optimization finance', 162 | 'portfolio optimization trading', 163 | 'portfolio construction finance', 164 | 'portfolio construction trading' 165 | ], 166 | category, 167 | min_stars_number=min_stars_number 168 | ) 169 | elif category == 'Factor and Risk Analysis': 170 | combined_df = search_repo_multiple_terms(['risk factor finance', 171 | 'risk factor trading', 172 | 'risk premia factor finance', 173 | 'risk premia factor trading', 174 | 'style factor finance', 175 | 'style factor trading', 176 | 'macro factor finance', 177 | 'macro factor trading', 178 | ], 179 | category, 180 | min_stars_number=int(min_stars_number * 0.05) 181 | ) 182 | elif category == 'Unsupervised': 183 | combined_df = search_repo_multiple_terms(['unsupervised finance', 184 | 'unsupervised trading' 185 | ], 186 | category, 187 | min_stars_number=int(min_stars_number * 0.1) 188 | ) 189 | elif category == 'Textual': 190 | combined_df = search_repo_multiple_terms(['NLP finance', 191 | 'NLP trading' 192 | ], 193 | category, 194 | min_stars_number=min_stars_number 195 | ) 196 | elif category == 'Derivatives and Hedging': 197 | combined_df = search_repo_multiple_terms(['derivatives finance', 198 | 'derivatives trading', 199 | 'quantlib trading', 200 | 'quantlib finance', 201 | 'hedging finance', 202 | 'hedging trading', 203 | 'option trading', 204 | 'option finance', 205 | 'delta hedge trading', 206 | 'delta hedge finance' 207 | ], 208 | category, 209 | min_stars_number=min_stars_number 210 | ) 211 | elif category == 'Fixed Income': 212 | combined_df = search_repo_multiple_terms(['corporate bond finance', 213 | 'corporate bond trading', 214 | 'muni bond trading', 215 | 'muni bond finance', 216 | 'investment grade finance', 217 | 'investment grade trading', 218 | 'high yield trading', 219 | 'high yield finance', 220 | 'credit rating trading', 221 | 'credit rating finance', 222 | 'fixed income trading', 223 | 'fixed income finance', 224 | 'corporate bond', 225 | 'muni bond', 226 | 'credit rating' 227 | ], 228 | category, 229 | min_stars_number=int(min_stars_number * 0.2) 230 | ) 231 | elif category == 'Alternative Finance': 232 | # don't include crypto here as it will skew the results, consider putting it as a seperate category 233 | combined_df = search_repo_multiple_terms(['private equity', 234 | 'venture capital', 235 | 'real estate trading', 236 | 'real estate finance', 237 | 'alternative asset trading', 238 | 'alternative asset finance', 239 | 'commodity trading', 240 | 'commodity finance', 241 | 'farmland finance', 242 | 'farmland trading' 243 | ], 244 | category, 245 | min_stars_number=int(min_stars_number * 0.5) 246 | ) 247 | elif category == 'Extended Research': 248 | combined_df = search_repo_multiple_terms(['fraud detection', 249 | 'behavioural finance', 250 | 'corporate finance', 251 | 'financial economics', 252 | 'mathematical finance', 253 | 'liquidity finance', 254 | 'fx trading', 255 | 'company life cycle', 256 | 'merger and acquisition', 257 | 'farmland trading', 258 | 'HFT', 259 | 'high frequency trading' 260 | ], 261 | category, 262 | min_stars_number=int(min_stars_number * 0.5) 263 | ) 264 | elif category == 'Courses': 265 | combined_df = search_repo_multiple_terms(['finance courses', 266 | 'machine learning courses', 267 | 'quantitative finance courses', 268 | 'time series courses', 269 | 'data science courses', 270 | 'financial engineering courses' 271 | ], 272 | category, 273 | min_stars_number=min_stars_number * 2 274 | ) 275 | elif category == 'Data': 276 | combined_df = search_repo_multiple_terms(['financial data', 277 | 'time series data', 278 | 'company fundamental data', 279 | 'crypto data', 280 | 'earnings data', 281 | 'fixed income data', 282 | 'fx data', 283 | 'etf data', 284 | 'finance database', 285 | 'sec edgar', 286 | 'economic data', 287 | 'investment data', 288 | 'fund data', 289 | 'options data', 290 | 'financial index data', 291 | 'futures data', 292 | 'cryptocurrencies data', 293 | 'money market data' 294 | ], 295 | category, 296 | min_stars_number=min_stars_number 297 | ) 298 | 299 | # only find ones that need to be inserted 300 | if combined_df is not None and not combined_df.empty and existing_repo_df is not None: 301 | combined_df = combined_df[ 302 | ~combined_df['repo_path'].str.lower().isin(existing_repo_df['repo_path'].dropna().str.lower())] 303 | 304 | return combined_df 305 | 306 | 307 | def search_new_repo_and_append(min_stars_number: int = 100, filter_list=None): 308 | """ 309 | 310 | :param min_stars_number: 311 | :param filter_list: 312 | """ 313 | repo_df = get_repo_list() 314 | category_list = repo_df['category'].unique().tolist() 315 | if filter_list is not None: 316 | category_list = [x for x in category_list if x in filter_list] 317 | 318 | new_repo_list = [] 319 | for category in category_list: 320 | combined_df = search_new_repo_by_category(category, min_stars_number, repo_df) 321 | if combined_df is not None: 322 | new_repo_list.append(combined_df) 323 | new_repo_df = pd.concat(new_repo_list).reset_index(drop=True) 324 | # drop duplicate regardless of the category, keep first one for now 325 | new_repo_df = new_repo_df.drop_duplicates(subset='repo_path') 326 | 327 | final_df = pd.concat([repo_df, new_repo_df]).reset_index(drop=True) 328 | 329 | final_df = final_df.sort_values(by='category') 330 | final_df.to_csv(os.path.join(PROJECT_ROOT_DIR, 'raw_data', 'url_list.csv'), index=False) 331 | 332 | 333 | def search_new_repo_by_category_per_day(min_stars_number: int = 100): 334 | repo_df = get_repo_list() 335 | category_list = repo_df['category'].unique().tolist() 336 | # based on today's date, pick which category to search to get around api limit 337 | current_date = datetime.datetime.today() 338 | n_category = len(category_list) 339 | days_in_week = 7 340 | if n_category % days_in_week == 0: 341 | n_repo_to_process_per_day = int(n_category / days_in_week) 342 | else: 343 | n_repo_to_process_per_day = int(n_category / days_in_week) + 1 344 | today_selection = current_date.weekday() 345 | repo_to_process = category_list[ 346 | today_selection * n_repo_to_process_per_day:(today_selection + 1) * n_repo_to_process_per_day] 347 | 348 | search_new_repo_and_append(min_stars_number=min_stars_number, filter_list=repo_to_process) 349 | 350 | 351 | if __name__ == '__main__': 352 | search_new_repo_by_category_per_day(min_stars_number=100) 353 | -------------------------------------------------------------------------------- /git_status.py: -------------------------------------------------------------------------------- 1 | import os 2 | from conf import PROJECT_ROOT_DIR 3 | import re 4 | import pandas as pd 5 | 6 | from git_util import get_repo_attributes_dict, get_github_client, get_repo_path 7 | 8 | 9 | def get_repo_list(): 10 | repo_df = pd.read_csv(os.path.join(PROJECT_ROOT_DIR, 'raw_data', 'url_list.csv')) 11 | if 'repo_path' not in repo_df.columns: 12 | repo_df['repo_path'] = repo_df['url'].apply(get_repo_path) 13 | return repo_df 14 | 15 | 16 | def get_repo_status(): 17 | g = get_github_client() 18 | repo_df = get_repo_list() 19 | for idx, row in repo_df.iterrows(): 20 | repo_path = row['repo_path'] 21 | if not pd.isna(repo_path): 22 | try: 23 | print('processing [{}]'.format(repo_path)) 24 | repo = g.get_repo(repo_path) 25 | 26 | repo_attr_dict = get_repo_attributes_dict(repo) 27 | except Exception as ex: 28 | print(ex) 29 | repo_attr_dict = {} 30 | 31 | for k, v in iter(repo_attr_dict.items()): 32 | repo_df.loc[idx, k] = v 33 | repo_df.to_csv(os.path.join(PROJECT_ROOT_DIR, 'raw_data', 'url_list.csv'), index=False) 34 | 35 | 36 | @DeprecationWarning 37 | def parse_readme_md(): 38 | """ 39 | 40 | :return: 41 | usage: 42 | >>> df = parse_readme_md() 43 | >>> df.to_csv(os.path.join(PROJECT_ROOT_DIR, 'raw_data', 'url_list.csv'), index=False) 44 | """ 45 | file_path = os.path.join(PROJECT_ROOT_DIR, 'README.md') 46 | with open(file_path) as f: 47 | lines = f.readlines()[11:] # skip heading 48 | all_df_list = [] 49 | for line_num in range(len(lines)): 50 | line = lines[line_num] 51 | if line.strip().startswith('#'): 52 | # find a heading 53 | heading = line.strip().replace('#', '').replace('\n', '').strip() 54 | # parse until next # or eof 55 | parsed_list = [] 56 | line_num += 1 57 | while line_num < len(lines) and not lines[line_num].strip().startswith('#'): 58 | link_line = lines[line_num].replace('\n', '').strip() 59 | if len(link_line) > 0: 60 | # usually in the format of '- [NAME](link) - comment 61 | split_sections = link_line.split('- ') 62 | if len(split_sections) == 2: 63 | comment_str = None 64 | elif len(split_sections) >= 3: 65 | comment_str = '-'.join(split_sections[2:]).strip() 66 | else: 67 | raise Exception('link_line [{}] not supported'.format(link_line)) 68 | 69 | title_and_link = split_sections[1].strip() 70 | title = re.search(r'\[(.*?)\]', title_and_link) 71 | title_str = None 72 | if title is not None: 73 | title_str = title.group(1) 74 | title_and_link = title_and_link.replace('[{}]'.format(title_str), '') 75 | m_link = re.search(r'\((.*?)\)', title_and_link) 76 | link_str = None 77 | if m_link is not None: 78 | link_str = m_link.group(1) 79 | parsed_set = (title_str, link_str, comment_str) 80 | parsed_list.append(parsed_set) 81 | line_num += 1 82 | parsed_df = pd.DataFrame(parsed_list, columns=['name', 'url', 'comment']) 83 | parsed_df['category'] = heading 84 | all_df_list.append(parsed_df) 85 | final_df = pd.concat(all_df_list).reset_index(drop=True) 86 | return final_df 87 | 88 | 89 | if __name__ == '__main__': 90 | get_repo_status() 91 | -------------------------------------------------------------------------------- /git_util.py: -------------------------------------------------------------------------------- 1 | from github import Github, Repository, GithubException 2 | import os 3 | import datetime 4 | 5 | 6 | def get_github_client(): 7 | # search for app_client and client secrets first, since this allow higher api request limit 8 | github_app = os.environ.get('GIT_APP_ID') 9 | if github_app is None: 10 | github_token = os.environ.get('GIT_TOKEN') 11 | g = Github(github_token) 12 | else: 13 | github_app_secret = os.environ.get('GIT_APP_SECRET') 14 | g = Github( 15 | client_id=github_app, 16 | client_secret=github_app_secret) 17 | return g 18 | 19 | 20 | # ******* 21 | # repo specific information 22 | # ******* 23 | def get_repo_path(in_url): 24 | repo_path = None 25 | if 'https://github.com/' in in_url: 26 | url_query = in_url.replace('https://github.com/', '') 27 | repo_path = '/'.join(url_query.split('/')[:2]) 28 | return repo_path 29 | 30 | 31 | def get_last_commit_date(input_repo: Repository): 32 | """ 33 | get latest commit from repo 34 | :param input_repo: 35 | :return: 36 | """ 37 | page = input_repo.get_commits().get_page(0)[0] 38 | return page.commit.author.date 39 | 40 | 41 | def get_repo_attributes_dict(input_repo: Repository, last_commit_within_years: int = 2): 42 | result_dict = {} 43 | try: 44 | result_dict = { 45 | 'repo_path': input_repo.full_name, 46 | 'created_at': input_repo.created_at, 47 | 'last_commit': get_last_commit_date(input_repo), 48 | 'last_update': input_repo.updated_at, 49 | 'star_count': input_repo.stargazers_count, 50 | 'fork_count': input_repo.forks_count, 51 | 'contributors_count': input_repo.get_contributors().totalCount 52 | 53 | } 54 | today = datetime.datetime.today() 55 | check_start_date = datetime.datetime(today.year - last_commit_within_years, 56 | today.month, 57 | today.day) 58 | 59 | if result_dict['last_commit'] >= check_start_date: 60 | repo_status = 'active' 61 | else: 62 | repo_status = 'inactive' 63 | result_dict['repo_status'] = repo_status 64 | except Exception as e: 65 | print(e) 66 | 67 | return result_dict 68 | -------------------------------------------------------------------------------- /raw_data/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/firmai/financial-machine-learning/a0fda6ac1f40251b9eb7cc32dd665db59130714e/raw_data/__init__.py -------------------------------------------------------------------------------- /raw_data/process.drawio: -------------------------------------------------------------------------------- 1 | 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-------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | pandas==1.2.1 2 | PyGithub==1.54.1 3 | tabulate==0.8.9 -------------------------------------------------------------------------------- /wiki_gen.py: -------------------------------------------------------------------------------- 1 | from conf import PROJECT_ROOT_DIR 2 | import os 3 | import pandas as pd 4 | import numpy as np 5 | import re 6 | 7 | from git_status import get_repo_list 8 | 9 | 10 | def get_wiki_status_color(input_text): 11 | if input_text is None or input_text == 'inactive': 12 | result_text = ":heavy_multiplication_x:" 13 | else: 14 | result_text = ":heavy_check_mark:" 15 | return '{}'.format(result_text) 16 | 17 | 18 | def get_wiki_rating(input_rating): 19 | result_text = '' 20 | if input_rating is not None and not np.isnan(input_rating): 21 | rating = int(input_rating) 22 | result_text = ':star:x{}'.format(rating) 23 | return '{}'.format(result_text) 24 | 25 | 26 | def generate_wiki_per_category(output_path, update_readme: bool = True): 27 | """ 28 | 29 | :param update_readme: 30 | :param output_path: 31 | """ 32 | repo_df = get_repo_list() 33 | for category in repo_df['category'].unique(): 34 | category_df = repo_df[repo_df['category'] == category].copy() 35 | url_md_list = [] 36 | for idx, irow in category_df[['name', 'url']].iterrows(): 37 | url_md_list.append('[{}]({})'.format(irow['name'], irow['url'])) 38 | 39 | formatted_df = pd.DataFrame({ 40 | 'repo': url_md_list, 41 | 'comment': category_df['comment'].apply(lambda x: '{}'.format(x)), 42 | 'created_at': category_df['created_at'].apply(lambda x: '{}'.format(x)), 43 | 'last_commit': category_df['last_commit'].apply(lambda x: '{}'.format(x)), 44 | 'star_count': category_df['star_count'].apply(lambda x: '{}'.format(x)), 45 | 'repo_status': category_df['repo_status'], 46 | 'rating': category_df['rating'] 47 | }) 48 | # add color for the status 49 | formatted_df = formatted_df.sort_values(by=['rating', 'star_count'], ascending=False).reset_index(drop=True) 50 | formatted_df['repo_status'] = formatted_df['repo_status'].apply(lambda x: get_wiki_status_color(x)) 51 | formatted_df['rating'] = formatted_df['rating'].apply(lambda x: get_wiki_rating(x)) 52 | formatted_df.columns = ['{}'.format(x) for x in formatted_df.columns] 53 | 54 | clean_category_name = category.lower().replace(' ', '_') 55 | output_path_full = os.path.join(output_path, '{}.md'.format(clean_category_name)) 56 | with open(output_path_full, 'w') as f: 57 | f.write(formatted_df.to_markdown(index=False)) 58 | print('wiki generated in [{}]'.format(output_path_full)) 59 | 60 | if update_readme: 61 | check_str = '[PLACEHOLDER_START:{}]'.format(clean_category_name) 62 | with open(os.path.join(PROJECT_ROOT_DIR, 'README.md')) as f: 63 | all_read_me = f.read() 64 | if check_str not in all_read_me: 65 | print(f'section {check_str} not found') 66 | continue 67 | 68 | # only display top 5, then expandable for extra 5 69 | with open(os.path.join(PROJECT_ROOT_DIR, 'README.md'), 'w') as f: 70 | 71 | table_str = formatted_df.iloc[:15].to_markdown(index=False) 72 | new_str = f" \n" 73 | new_str += table_str 74 | new_str += f"" 75 | 76 | search_start = re.escape(''.format(clean_category_name)) 77 | search_end = re.escape(''.format(clean_category_name)) 78 | pattern_s = re.compile(r'{}.*?{}'.format(search_start, search_end), re.DOTALL) 79 | write_str = re.sub(pattern_s, new_str, all_read_me) 80 | f.write(write_str) 81 | 82 | 83 | if __name__ == '__main__': 84 | local_path = os.path.join(PROJECT_ROOT_DIR, 'generated_wiki') 85 | generate_wiki_per_category(local_path) 86 | --------------------------------------------------------------------------------