├── .gitignore ├── LICENSE └── README.md /.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 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 Ignito 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Data and ML Projects 2 | This repository contains projects covering Data Analytics, Data Science, Data Engineering, Machine Learning, MLOPs 3 | 4 | ![YDANG](https://user-images.githubusercontent.com/104568275/209964432-67655f8e-081b-4bd9-963d-eb07f2fea072.png) 5 | 6 | Youtube for all the implemented projects and tech interview resources - [Ignito Youtube Channel](https://www.youtube.com/@ignito5917/about) 7 | 8 | [Complete Cheat Sheet for Tech Interviews - How to prepare efficiently](https://open.substack.com/pub/naina0405/p/cheat-sheet-for-tech-interviews-how-339?r=14q3sp&utm_campaign=post&utm_medium=web) 9 | 10 | [Mega Launch - 200+ System Design Case Studies](https://open.substack.com/pub/naina0405/p/mega-launch-200-new-system-design?r=14q3sp&utm_campaign=post&utm_medium=web) 11 | 12 | [System Design Most Important Terms](https://medium.com/coders-mojo/day-19-of-system-design-series-system-design-important-terms-45002fbbb789?sk=dab9718bca1b3676f093a759c89dea2c) 13 | 14 | [System Design Template](https://medium.com/coders-mojo/day-3-of-system-design-case-studies-series-875df4b766b9?sk=1133c9135f849f4497400a6b9caf5c2e) 15 | 16 | [Complete System Design Case Studies ](https://medium.com/coders-mojo/day-1-of-system-design-case-studies-series-b3c3fecae079?sk=ee7333918f135e06eb3a9b9434d35696) 17 | 18 | [How to solve any System Design Question ( approach that you should take)](https://medium.com/coders-mojo/day-2-of-system-design-case-studies-series-ccd8899c6e6b?sk=9e95d3979ac4f995dec397c49ab8e05d) 19 | 20 | [ML System Design Case Studies Series](https://bit.ly/3i5EDiH) 21 | 22 | For Data Structures and Algorithms, start here : [Day 1 of 30 days of Data Structures and Algorithms and System Design Simplified : DSA and System Design made Easy](https://medium.com/coders-mojo/day-1-of-30-days-of-data-structures-and-algorithms-and-system-design-simplified-dsa-and-system-965e860ec677?sk=aa49bdbc46a72f600cb51774f0aea6b6) 23 | 24 | ---------- 25 | 26 | For 30 days of Data Analytics with projects Series : [Start here](https://medium.com/coders-mojo/day-1-of-30-days-of-data-analytics-with-projects-series-6c2f939ec865?sk=55671d964311268ae548dbdac902ebe5) 27 | 28 | For 60 days of Data Science and Machine Learning with projects Series: [Start here](https://medium.com/coders-mojo/data-science-and-ml-projects-series-d9b07789368b?sk=4f1aaffd6d9dcf0255b7e02139d3dc71) 29 | 30 | # Data Analytics Projects 31 | 32 | [Project 1](https://medium.com/coders-mojo/day-11-of-30-days-of-data-analytics-with-projects-series-c0bcba787dc3?sk=cc7d4d8d7c1382a47ccbd5c43df3fc31) 33 | 34 | [Project 2](https://medium.com/coders-mojo/project-day-16-of-30-days-of-data-analytics-with-projects-series-6992a946c868?sk=0be0825d7d944a67fc779fea277c0f98) 35 | 36 | [Project 3](https://medium.com/coders-mojo/project-3-day-17-of-30-days-of-data-analytics-with-projects-series-a76e254a4b65?sk=0b141a399d22f44c85975ec285efb95b) 37 | 38 | [Project 4](https://medium.com/coders-mojo/project-4-day-18-of-30-days-of-data-analytics-with-projects-series-614b8a575d32?sk=2ca301772f1048d767a9947fc3caefda) 39 | 40 | [Project 5](https://medium.com/coders-mojo/project-5-day-19-of-30-days-of-data-analytics-with-projects-series-407255f6ab56?sk=bf8aa373bd2d3611b7f6ee384025a925) 41 | 42 | [Project 6](https://medium.com/coders-mojo/project-6-day-20-of-30-days-of-data-analytics-with-projects-series-7f80a9753354?sk=97746824884dbab0803e69170df937b2) 43 | 44 | [Project 7](https://medium.com/coders-mojo/project-7-day-21-of-30-days-of-data-analytics-with-projects-series-ce24f02de56f?sk=66b7bfb40c9aaaf897ed8d7373d85bf6) 45 | 46 | [Project 8](https://medium.com/coders-mojo/project-8-day-22-of-30-days-of-data-analytics-with-projects-series-dc8f463adac6?sk=2a7ac02cb6f0c6be7568c1ba5c2552b5) 47 | 48 | [Project 9](https://medium.com/coders-mojo/project-9-day-23-of-30-days-of-data-analytics-with-projects-series-6747f695d570?sk=9c51bec759e96404208cebf448409adc) 49 | 50 | [Project 10](https://medium.com/coders-mojo/project-10-day-24-of-30-days-of-data-analytics-with-projects-series-7614ea846ab0?sk=3ff451f1dd67c846b5064395dde49f0a) 51 | 52 | [Project 11](https://medium.com/coders-mojo/project-11-day-25-of-30-days-of-data-analytics-with-projects-series-ee6f16db5d59?sk=d6a03230090f77bcadc2918207899cd0) 53 | 54 | # Data Science and Machine Learning Projects 55 | 56 | [Project 1](https://medium.datadriveninvestor.com/day-21-60-days-of-data-science-and-machine-learning-series-b0feb6ba71f4) 57 | 58 | [Project 2](https://medium.com/coders-mojo/day-28-60-days-of-data-science-and-machine-learning-series-ee7e4f3b6b46) 59 | 60 | [Project 3](https://medium.com/coders-mojo/day-29-60-days-of-data-science-and-machine-learning-series-a31184450ce5) 61 | 62 | [Project 4](https://medium.com/coders-mojo/day-30-60-days-of-data-science-and-machine-learning-series-823fa9447928) 63 | 64 | [Project 5](https://medium.datadriveninvestor.com/recurrent-neural-network-with-keras-b5b5f6fe5187) 65 | 66 | [Project 6](https://medium.datadriveninvestor.com/clustering-geolocation-data-in-python-using-dbscan-and-k-means-3705d9f44522) 67 | 68 | [Project 7](https://medium.datadriveninvestor.com/facial-expression-recognition-using-keras-cbdd661a0a54) 69 | 70 | [Project 8](https://medium.datadriveninvestor.com/hyperparameter-tuning-with-keras-tuner-3a609d3fd85b) 71 | 72 | [Project 9](https://medium.datadriveninvestor.com/custom-layers-in-keras-de5f793217aa) 73 | 74 | [Project 10](https://medium.datadriveninvestor.com/build-machine-learning-pipelines-with-code-part-1-bd3ed7152124) 75 | 76 | [Project 11](https://medium.datadriveninvestor.com/read-and-process-large-datasets-within-seconds-part-1-b4b12c261b2c) 77 | 78 | [Project 12](https://medium.datadriveninvestor.com/analyzing-video-using-python-opencv-and-numpy-5471cab200c4) 79 | 80 | [Project 13](https://medium.datadriveninvestor.com/day-27-60-days-of-data-science-and-machine-learning-series-4c4b7fe6af7) 81 | 82 | [Project 14](https://medium.com/coders-mojo/day-31-60-days-of-data-science-and-machine-learning-series-7c211301bab0) 83 | 84 | [Project 15](https://medium.com/coders-mojo/day-32-60-days-of-data-science-and-machine-learning-series-c4a1205d37ff) 85 | 86 | [Project 16](https://medium.com/coders-mojo/day-33-60-days-of-data-science-and-machine-learning-series-79830d11b365) 87 | 88 | [Project 17](https://medium.com/coders-mojo/day-34-60-days-of-data-science-and-machine-learning-series-420df19d1ec0) 89 | 90 | [Project 18](https://medium.com/coders-mojo/day-35-60-days-of-data-science-and-machine-learning-series-63819382660) 91 | 92 | [Project 19](https://medium.com/coders-mojo/day-36-60-days-of-data-science-and-machine-learning-series-7219a2bf77fc) 93 | 94 | [Project 20](https://medium.com/coders-mojo/day-38-60-days-of-data-science-and-machine-learning-series-6f9175b0d12) 95 | 96 | [Project 21](https://medium.com/coders-mojo/day-39-60-days-of-data-science-and-machine-learning-series-95af4ac9ac68) 97 | 98 | [Project 22](https://medium.com/coders-mojo/day-40-60-days-of-data-science-and-machine-learning-series-2f1214969836) 99 | 100 | [Project 23](https://medium.com/coders-mojo/day-41-60-days-of-data-science-and-machine-learning-series-d0b6649587c9) 101 | 102 | [Project 24](https://medium.com/coders-mojo/day-42-60-days-of-data-science-and-machine-learning-series-d82a53d13cf7) 103 | 104 | [Project 25](https://medium.com/coders-mojo/day-43-60-days-of-data-science-and-machine-learning-series-299818452cea) 105 | 106 | [Project 26](https://medium.com/coders-mojo/day-44-60-days-of-data-science-and-machine-learning-series-eee5568c4e97) 107 | 108 | [Project 27](https://medium.com/coders-mojo/day-45-60-days-of-data-science-and-machine-learning-series-241136b9412e) 109 | 110 | [Project 28](https://medium.com/coders-mojo/day-46-60-days-of-data-science-and-machine-learning-series-c7bbbb6750b2) 111 | 112 | [Project 29](https://medium.com/coders-mojo/day-47-60-days-of-data-science-and-machine-learning-series-919df5d831db) 113 | 114 | [Project 30](https://medium.com/coders-mojo/day-48-60-days-of-data-science-and-machine-learning-series-b22b0c9bf384) 115 | 116 | [Project 31](https://medium.com/coders-mojo/day-49-60-days-of-data-science-and-machine-learning-series-311ab1d62bc2) 117 | 118 | [Project 32](https://medium.com/coders-mojo/day-50-60-days-of-data-science-and-machine-learning-series-33a30369d91a) 119 | 120 | [Project 33](https://medium.com/coders-mojo/day-51-60-days-of-data-science-and-machine-learning-series-b82a72fd1bd4) 121 | 122 | [Project 34](https://medium.com/coders-mojo/day-52-60-days-of-data-science-and-machine-learning-series-4e7788c3245e) 123 | 124 | [Project 35](https://medium.com/coders-mojo/day-53-60-days-of-data-science-and-machine-learning-series-d42724810a11) 125 | 126 | [Project 36](https://medium.com/coders-mojo/day-54-60-days-of-data-science-and-machine-learning-series-86491f964a0e) 127 | 128 | [Project 37](https://medium.com/coders-mojo/day-55-60-days-of-data-science-and-machine-learning-series-7393ff714992) 129 | 130 | [Project 38](https://medium.com/coders-mojo/day-56-60-days-of-data-science-and-machine-learning-series-71774a7fe5a1) 131 | 132 | [Project 39](https://medium.com/coders-mojo/day-57-60-days-of-data-science-and-machine-learning-series-43f3a687603c) 133 | 134 | [Project 40](https://medium.com/coders-mojo/day-58-60-days-of-data-science-and-machine-learning-series-2df3f4e03a55) 135 | 136 | [Project 41](https://medium.com/coders-mojo/day-59-60-days-of-data-science-and-machine-learning-series-3786d513fcbd) 137 | 138 | [Project 42](https://medium.com/coders-mojo/day-60-60-days-of-data-science-and-machine-learning-series-29f72bd88c8c) 139 | 140 | ------ 141 | 142 | # Some of the other best Series - 143 | 144 | [Complete 60 Days of Data Science and Machine Learning Series ](https://medium.com/coders-mojo/day-1-day-60-quick-recap-of-60-days-of-data-science-and-ml-6fc021643d1?sk=4e75e043b7630a9f963562ebac94e129) 145 | 146 | [30 days of Machine Learning Ops](https://medium.com/coders-mojo/day-1-of-30-days-of-machine-learning-ops-7c299e4b09be?sk=4ab48350a5c359fc157109e48b1d738f) 147 | 148 | [30 Days of Natural Language Processing ( NLP) Series](https://medium.com/coders-mojo/quick-recap-30-days-of-natural-language-processing-nlp-with-projects-series-ceb674e3c09b?sk=ca09b27b3d5867f23ab4dc367b6c0c32) 149 | 150 | [Data Science and Machine Learning Research ( papers) Simplified **](https://medium.com/coders-mojo/day-1-data-science-and-ml-research-papers-simplified-a68b00a3b1c4?sk=56136229ff738bd734f19d2b6953f78c) 151 | 152 | [30 days of Data Engineering with projects Series](https://medium.com/coders-mojo/day-1-of-30-days-of-data-engineering-894822fcb128?sk=76ba558bfe2d9f85cbe741e505295531) 153 | 154 | [60 days of Data Science and ML Series with projects](https://medium.com/coders-mojo/day-1-day-60-quick-recap-of-60-days-of-data-science-and-ml-6fc021643d1?sk=4e75e043b7630a9f963562ebac94e129) 155 | 156 | [100 days : Your Data Science and Machine Learning Degree Series with projects](https://medium.com/coders-mojo/100-days-your-data-science-and-ml-degree-part-3-c621ecfdf711?sk=1a8c7b0c204d73432d56b7d1a3a26474) 157 | 158 | [23 Data Science Techniques You Should Know](https://ai.plainenglish.io/23-data-science-techniques-you-should-know-61bc2c9d1b3a?sk=1680c36193eb22198974c9008d62a33c) 159 | 160 | [Tech Interview Series — Curated List of coding questions](https://medium.com/coders-mojo/mega-post-tech-interview-the-only-list-of-questions-you-need-to-practice-ee349ea197bb?sk=fac3614684daff4b50a70c0a71e4d528) 161 | 162 | [Complete System Design with most popular Questions Series](https://medium.com/coders-mojo/system-design-made-easy-quick-recap-of-complete-system-design-34af7e3aedfb?sk=bdd6a19edc1f3ce4a5064923f5b68721) 163 | 164 | [Complete Data Visualization and Pre-processing Series with projects](https://medium.com/coders-mojo/complete-data-preprocessing-and-data-visualization-with-projects-mega-compilation-part-2-41584ef0920e?sk=842390da51689b8d43148c3980570db0) 165 | 166 | [Complete Python Series with Projects](https://medium.com/coders-mojo/complete-python-and-projects-mega-compilation-7ec8f7adfe71?sk=ee0ecf43f23c6dd44dd35d984b3e5df4) 167 | 168 | [Complete Advanced Python Series with Projects](https://medium.com/coders-mojo/complete-advanced-python-with-projects-mega-compilation-part-6-729c1826032b?sk=7faffe20f8039fa57099f7a372b6d665) 169 | 170 | [Kaggle Best Notebooks that will teach you the most](https://medium.com/coders-mojo/my-list-of-kaggle-best-notebooks-topic-wise-data-science-and-machine-learning-part-2-84772863e9ae?sk=5ed02e419854a6c11add3ddc1e52947f) 171 | 172 | [Complete Developers Guide to Git](https://medium.datadriveninvestor.com/the-complete-developers-guide-to-git-6a23125996e1?sk=e30479bbe713930ea93018e1a46d9185) 173 | 174 | [Exceptional Github Repos — Part 1](https://medium.com/coders-mojo/6-exceptional-github-repos-for-all-developers-part-1-21e8fa04e150?sk=9140b249af6fe73d45717185fad48962) 175 | 176 | [Exceptional Github Repos — Part 2](https://medium.com/coders-mojo/6-exceptional-github-repos-for-all-developers-part-2-3eec9a68c31c?sk=8e31d0eb7eb1d2d0bbbcecaa66bd4e7e) 177 | 178 | [All the Data Science and Machine Learning Resources](https://medium.datadriveninvestor.com/best-resources-for-data-science-and-machine-learning-full-list-5ceb9a2791bf?sk=cf85b2cef95560c58509877a794577ff) 179 | 180 | [210 Machine Learning Projects](https://medium.datadriveninvestor.com/210-machine-learning-projects-with-source-code-that-you-can-build-today-721b035649e0?sk=da5f593572a0261a6314afad99a0356c) 181 | 182 | ------- 183 | 184 | 185 | # 6 Highly Recommended Data Science and Machine Learning Courses that you MUST take ( with certificate) -  186 | 187 | 1. Complete Data Scientist : https://bit.ly/3wiIo8u 188 | 189 | Learn to run data pipelines, design experiments , build recommendation systems, and deploy solutions to the cloud. 190 | 191 | ---- 192 | 193 | 2. Complete Data Engineering : https://bit.ly/3A9oVs5 194 | 195 | Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets 196 | 197 | ----- 198 | 199 | 3. Complete Machine Learning Engineer : https://bit.ly/3Tir8ub 200 | 201 | Learn advanced machine learning techniques and algorithms - including how to package and deploy your models to a production environment. 202 | 203 | ----- 204 | 205 | 4. Complete Data Product Manager : https://bit.ly/3QGUtwi 206 | 207 | Leverage data to build products that deliver the right experiences, to the right users, at the right time. Lead the development of data-driven products that position businesses to win in their market. 208 | 209 | ------ 210 | 211 | 5. Complete Natural Language Processing : https://bit.ly/3T7J8qY 212 | 213 | Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more. 214 | 215 | ------ 216 | 217 | 6. Complete Deep Learning: https://bit.ly/3T5ppIo 218 | 219 | Learn to implement Neural Networks using the deep learning framework PyTorch 220 | --------------------------------------------------------------------------------