├── .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) 2023 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 | # Implemented-Projects- 2 | 3 | Youtube for all the implemented projects and tech interview resources - [Ignito Youtube Channel](https://www.youtube.com/@ignito5917/about) 4 | 5 | [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) 6 | 7 | [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) 8 | 9 | [Complete System Design Github](https://github.com/Coder-World04/Complete-System-Design/blob/main/README.md) 10 | 11 | [I took theses Projects Based Courses to Build Industry aligned Data Science and ML skills](https://open.substack.com/pub/naina0405/p/i-took-theses-projects-based-courses-af3?r=14q3sp&utm_campaign=post&utm_medium=web) 12 | 13 | [Part 1 - How to solve Any ML System Design Problem](https://open.substack.com/pub/naina0405/p/part-1-how-to-solve-any-ml-system?r=14q3sp&utm_campaign=post&utm_medium=web) 14 | 15 | ------- 16 | 17 | This repository covers Implemented projects that you can build and add to your portfolio. 18 | 19 | [Implemented Project 1](https://medium.datadriveninvestor.com/day-21-60-days-of-data-science-and-machine-learning-series-b0feb6ba71f4?sk=c2a68682a01ea2de48b837f429032db1) 20 | 21 | [Implemented Project 2](https://medium.com/coders-mojo/day-28-60-days-of-data-science-and-machine-learning-series-ee7e4f3b6b46?sk=5df97300e1119756f04644326dc465d2) 22 | 23 | [Implemented Project 3](https://medium.com/coders-mojo/day-29-60-days-of-data-science-and-machine-learning-series-a31184450ce5?sk=505ce3f7bc3ac891cd794282fb8b29b7) 24 | 25 | [Implemented Project 4](https://medium.com/coders-mojo/day-30-60-days-of-data-science-and-machine-learning-series-823fa9447928?sk=9a336dd863dec82ddc5206a8127bf26a) 26 | 27 | [Implemented Project 5](https://medium.datadriveninvestor.com/recurrent-neural-network-with-keras-b5b5f6fe5187?sk=ebe280ef5805c93257d9cfd65016ce69) 28 | 29 | [Implemented Project 6](https://medium.datadriveninvestor.com/clustering-geolocation-data-in-python-using-dbscan-and-k-means-3705d9f44522?sk=660363b9cb33daf45ea9629bef3a6c02) 30 | 31 | [Implemented Project 7](https://medium.datadriveninvestor.com/facial-expression-recognition-using-keras-cbdd661a0a54?sk=d7e69c7b93d17f97986031664554bb9f) 32 | 33 | [Implemented Project 8](https://medium.datadriveninvestor.com/hyperparameter-tuning-with-keras-tuner-3a609d3fd85b?sk=4e0437f71ec0cd6d0c6f255cf22ef54b) 34 | 35 | [Implemented Project 9](https://medium.datadriveninvestor.com/custom-layers-in-keras-de5f793217aa?sk=f288316f1ea8362a6f7b8dc808898592) 36 | 37 | [Implemented Project 10](https://medium.datadriveninvestor.com/build-machine-learning-pipelines-with-code-part-1-bd3ed7152124?sk=ef7ee2c3ccd44a312cdcf3996dfa1248) 38 | 39 | [Implemented Project 11](https://medium.datadriveninvestor.com/read-and-process-large-datasets-within-seconds-part-1-b4b12c261b2c?sk=948d436420d8b53c009f73009e6f1ab0) 40 | 41 | [Implemented Project 12](https://medium.datadriveninvestor.com/analyzing-video-using-python-opencv-and-numpy-5471cab200c4?sk=c1cc14ea15d5afc428eb572b5a7bc065) 42 | 43 | [Implemented Project 13](https://medium.datadriveninvestor.com/day-27-60-days-of-data-science-and-machine-learning-series-4c4b7fe6af7?sk=15007aa27e98df7cfeed6f25f409ce73) 44 | 45 | [Implemented Project 14](https://medium.com/coders-mojo/day-31-60-days-of-data-science-and-machine-learning-series-7c211301bab0?sk=9f568f8bf24a40034baa2019f60700cb) 46 | 47 | [Implemented Project 15](https://medium.com/coders-mojo/day-32-60-days-of-data-science-and-machine-learning-series-c4a1205d37ff?sk=2c5996c42a046324c07f66d053ae5ed6) 48 | 49 | [Implemented Project 16](https://medium.com/coders-mojo/day-33-60-days-of-data-science-and-machine-learning-series-79830d11b365?sk=c1dea3eeec3071d5ffb0951e4d36fafc) 50 | 51 | [Implemented Project 17](https://medium.com/coders-mojo/day-34-60-days-of-data-science-and-machine-learning-series-420df19d1ec0?sk=d9e57b668a213027f14aeadde324ce51) 52 | 53 | [Implemented Project 18](https://medium.com/coders-mojo/day-35-60-days-of-data-science-and-machine-learning-series-63819382660?sk=3d326197d6726e9581f8976850c79093) 54 | 55 | [Implemented Project 19](https://medium.com/coders-mojo/day-36-60-days-of-data-science-and-machine-learning-series-7219a2bf77fc?sk=6a980c837bb478482a22b289976fb7e0) 56 | 57 | [Implemented Project 20](https://medium.com/coders-mojo/day-38-60-days-of-data-science-and-machine-learning-series-6f9175b0d12?sk=c9af00528219393aa8be72c4d2bb4b20) 58 | 59 | [Implemented Project 21](https://medium.com/coders-mojo/day-39-60-days-of-data-science-and-machine-learning-series-95af4ac9ac68?sk=e5acb35788e96d24c82e1b393620252a) 60 | 61 | [Implemented Project 22](https://medium.com/coders-mojo/day-40-60-days-of-data-science-and-machine-learning-series-2f1214969836?sk=0e6a1bf62bddc85215886111ec8b0277) 62 | 63 | [Implemented Project 23](https://medium.com/coders-mojo/day-41-60-days-of-data-science-and-machine-learning-series-d0b6649587c9?sk=c44ea1ed6f4859f083f536ace05e27a9) 64 | 65 | [Implemented Project 24](https://medium.com/coders-mojo/day-42-60-days-of-data-science-and-machine-learning-series-d82a53d13cf7?sk=47ed892a1e12ebf1532703a531b26293) 66 | 67 | [Implemented Project 25](https://medium.com/coders-mojo/day-43-60-days-of-data-science-and-machine-learning-series-299818452cea?sk=568ca9a371a4f871c3d59b5307ea5df5) 68 | 69 | [Implemented Project 26](https://medium.com/coders-mojo/day-44-60-days-of-data-science-and-machine-learning-series-eee5568c4e97?sk=118288c90b1fff8b9b856687f9e3f3e9) 70 | 71 | [Implemented Project 27](https://medium.com/coders-mojo/day-45-60-days-of-data-science-and-machine-learning-series-241136b9412e?sk=2c5239a326d9c67f3efb8a4f25c91d1e) 72 | 73 | [Implemented Project 28](https://medium.com/coders-mojo/day-46-60-days-of-data-science-and-machine-learning-series-c7bbbb6750b2?sk=be36d9560f6327c91049273dc5cfb533) 74 | 75 | [Implemented Project 29](https://medium.com/coders-mojo/day-47-60-days-of-data-science-and-machine-learning-series-919df5d831db?sk=2aaa0105edb308ad848fc1401409c2e1) 76 | 77 | [Implemented Project 30](https://medium.com/coders-mojo/day-48-60-days-of-data-science-and-machine-learning-series-b22b0c9bf384?sk=575e0cce7ddb294e4df7b58ebd4351a1) 78 | 79 | [Implemented Project 31](https://medium.com/coders-mojo/day-49-60-days-of-data-science-and-machine-learning-series-311ab1d62bc2?sk=00c4e3ad64694252dde51b98ac19fe39) 80 | 81 | [Implemented Project 32](https://medium.com/coders-mojo/day-50-60-days-of-data-science-and-machine-learning-series-33a30369d91a?sk=ad10b5f561e40601ded81a91be47a602) 82 | 83 | [Implemented Project 33](https://medium.com/coders-mojo/day-51-60-days-of-data-science-and-machine-learning-series-b82a72fd1bd4?sk=d7db4e220d1c5750de39d81fefb727a1) 84 | 85 | [Implemented Project 34](https://medium.com/coders-mojo/day-52-60-days-of-data-science-and-machine-learning-series-4e7788c3245e?sk=276a83deab30c5b2557ecba7d699de19) 86 | 87 | [Implemented Project 35](https://medium.com/coders-mojo/day-53-60-days-of-data-science-and-machine-learning-series-d42724810a11?sk=b602347b08c68f8a300157b5143f4836) 88 | 89 | [Implemented Project 36](https://medium.com/coders-mojo/day-54-60-days-of-data-science-and-machine-learning-series-86491f964a0e?sk=5eb7052ad3d89eea4bb6c900ac303832) 90 | 91 | [Implemented Project 37](https://medium.com/coders-mojo/day-55-60-days-of-data-science-and-machine-learning-series-7393ff714992?sk=55fde451668f707c032dc07bf7b9484c) 92 | 93 | [Implemented Project 38](https://medium.com/coders-mojo/day-56-60-days-of-data-science-and-machine-learning-series-71774a7fe5a1?sk=3bd042131f85cdf0d67a85b21a518226) 94 | 95 | [Implemented Project 39](https://medium.com/coders-mojo/day-57-60-days-of-data-science-and-machine-learning-series-43f3a687603c?sk=6d0ce606aa412e1228d2b342877dd3e1) 96 | 97 | [Implemented Project 40](https://medium.com/coders-mojo/day-58-60-days-of-data-science-and-machine-learning-series-2df3f4e03a55?sk=5aca4a5e6b32d752906bfc9b17a4c12c) 98 | 99 | [Implemented Project 41](https://medium.com/coders-mojo/day-59-60-days-of-data-science-and-machine-learning-series-3786d513fcbd?sk=b7480e7a65c5c90e529820ebfbb6470c) 100 | 101 | [Implemented Project 42](https://medium.com/coders-mojo/day-60-60-days-of-data-science-and-machine-learning-series-29f72bd88c8c?sk=51ad2dfc53fabcc6dad62112c13badc9) 102 | 103 | [Implemented Project 43](https://medium.com/coders-mojo/day-11-of-30-days-of-data-analytics-with-projects-series-c0bcba787dc3?sk=cc7d4d8d7c1382a47ccbd5c43df3fc31) 104 | 105 | [Implemented Project 44](https://medium.com/coders-mojo/project-day-16-of-30-days-of-data-analytics-with-projects-series-6992a946c868?sk=0be0825d7d944a67fc779fea277c0f98) 106 | 107 | [Implemented Project 45](https://medium.com/coders-mojo/project-3-day-17-of-30-days-of-data-analytics-with-projects-series-a76e254a4b65?sk=0b141a399d22f44c85975ec285efb95b) 108 | 109 | [Implemented Project 46](https://medium.com/coders-mojo/project-4-day-18-of-30-days-of-data-analytics-with-projects-series-614b8a575d32?sk=2ca301772f1048d767a9947fc3caefda) 110 | 111 | [Implemented Project 47](https://medium.com/coders-mojo/project-5-day-19-of-30-days-of-data-analytics-with-projects-series-407255f6ab56?sk=bf8aa373bd2d3611b7f6ee384025a925) 112 | 113 | [Implemented Project 48](https://medium.com/coders-mojo/project-6-day-20-of-30-days-of-data-analytics-with-projects-series-7f80a9753354?sk=97746824884dbab0803e69170df937b2) 114 | 115 | [Implemented Project 49](https://medium.com/coders-mojo/project-7-day-21-of-30-days-of-data-analytics-with-projects-series-ce24f02de56f?sk=66b7bfb40c9aaaf897ed8d7373d85bf6) 116 | 117 | [Implemented Project 50](https://medium.com/coders-mojo/project-8-day-22-of-30-days-of-data-analytics-with-projects-series-dc8f463adac6?sk=2a7ac02cb6f0c6be7568c1ba5c2552b5) 118 | 119 | [Implemented Project 51](https://medium.com/coders-mojo/project-9-day-23-of-30-days-of-data-analytics-with-projects-series-6747f695d570?sk=9c51bec759e96404208cebf448409adc) 120 | 121 | [Implemented Project 52](https://medium.com/coders-mojo/project-10-day-24-of-30-days-of-data-analytics-with-projects-series-7614ea846ab0?sk=3ff451f1dd67c846b5064395dde49f0a) 122 | 123 | [Implemented Project 53](https://medium.com/coders-mojo/project-11-day-25-of-30-days-of-data-analytics-with-projects-series-ee6f16db5d59?sk=d6a03230090f77bcadc2918207899cd0) 124 | 125 | # Projects 126 | ----------------- 127 | 128 | [Implemented Data Science and ML projects](https://medium.com/coders-mojo/data-science-and-ml-projects-series-d9b07789368b?sk=4f1aaffd6d9dcf0255b7e02139d3dc71) 129 | 130 | [Implemented Data Analytics projects](https://medium.com/coders-mojo/data-analytics-projects-series-b6abc25e4815?sk=571e1a7e344560ab7aa01d7af7004824) 131 | 132 | [Implemented Deep Learning Projects](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 133 | 134 | [Complete ML Research Papers Summarized](https://medium.com/coders-mojo/complete-ml-research-papers-summarized-a69afd5bb9bf?sk=54dcfdc31cf7c959192ebf666ca24cdd) 135 | 136 | [Implemented Machine Learning Ops Projects](https://medium.com/coders-mojo/implemented-machine-learning-ops-projects-60b9414cd8c3?sk=6e1a5000842aafe7d39f5f5bb0df1544) 137 | 138 | [Implemented Time Series Analysis and Forecasting Projects](https://medium.com/coders-mojo/implemented-time-series-analysis-and-forecasting-projects-3adea88b7fe8?sk=7c05f325b2a14a44c84c4832a91a7be9) 139 | 140 | [Implemented Applied Machine Learning Projects](https://medium.com/coders-mojo/implemented-applied-machine-learning-projects-95294db9cd5?sk=a418f26d2b07b86cecbed625b5570ce8) 141 | 142 | [Implemented Tensorflow and Keras Projects](https://medium.com/coders-mojo/implemented-tensorflow-and-keras-projects-adbaed77d572?sk=dab9d9584be3eb7a63125b871515e0e4) 143 | 144 | [Implemented PyTorch Projects](https://medium.com/coders-mojo/implemented-pytorch-projects-f434f6faed4d?sk=baaae01f83ed39a9517d8ad58d8d9606) 145 | 146 | [Implemented Scikit Learn Projects](https://medium.com/coders-mojo/implemented-scikit-learn-projects-c0e65f70e54e?sk=819c5487448cb84eafa75589a6a770cd) 147 | 148 | [Implemented Big Data Projects](https://medium.com/coders-mojo/implemented-big-data-projects-9973d14131ca?sk=f41dfc9c96be347127ab78ac998e06ee) 149 | 150 | [Implemented Cloud Machine Learning Projects](https://medium.com/coders-mojo/implemented-cloud-machine-learning-projects-b5a34d1d7f8?sk=6fa9d02dde908aa397dcaeb02cf754b4) 151 | 152 | [Implemented Neural Networks Projects](https://medium.com/coders-mojo/implemented-neural-networks-projects-d25a6476d72b?sk=022a810763e8e8366974c066fa9c1c85) 153 | 154 | [Implemented OpenCV Projects](https://medium.com/coders-mojo/implemented-opencv-projects-7406d9b89032?sk=eea2d41edcb2da4a87830dfb7d702524) 155 | 156 | [Implemented Data Visualization Projects](https://medium.com/coders-mojo/implemented-data-visualization-projects-9576431db13d?sk=280a40c65eced3fd9febd11a40d68bf0) 157 | 158 | [Implemented Data Mining Projects](https://medium.com/coders-mojo/implemented-data-mining-projects-b448780b5869?sk=a41f09a7fe9c71566977dfd47ed76e9f) 159 | 160 | [Implemented Data Engineering Projects](https://medium.com/coders-mojo/implemented-data-engineering-projects-59a8c4190b28?sk=d08d3f406f1dddd6d8122c03ca4fef5d) 161 | 162 | [Implemented Natural Leaning Processing Projects](https://medium.com/coders-mojo/implemented-natural-leaning-processing-projects-f5efa8c4cb31?sk=597f814c51b392abd8b2a9e28c1eebb5) 163 | 164 | ---- 165 | # Highly Recommended Data Science and Machine Learning Courses that you MUST take ( with certificate) -  166 | 167 | 1. Complete Data Scientist : https://bit.ly/3wiIo8u 168 | 169 | Learn to run data pipelines, design experiments , build recommendation systems, and deploy solutions to the cloud. 170 | 171 | ---- 172 | 173 | 2. Complete Data Engineering : https://bit.ly/3A9oVs5 174 | 175 | Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets 176 | 177 | ----- 178 | 179 | 3. Complete Machine Learning Engineer : https://bit.ly/3Tir8ub 180 | 181 | Learn advanced machine learning techniques and algorithms - including how to package and deploy your models to a production environment. 182 | 183 | ----- 184 | 185 | 4. Complete Data Product Manager : https://bit.ly/3QGUtwi 186 | 187 | 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. 188 | 189 | ------ 190 | 191 | 5. Complete Natural Language Processing : https://bit.ly/3T7J8qY 192 | 193 | Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more. 194 | 195 | ------ 196 | 197 | 6. Complete Deep Learning: https://bit.ly/3T5ppIo 198 | 199 | Learn to implement Neural Networks using the deep learning framework PyTorch 200 | 201 | ------ 202 | 203 | --------------------------------------------------------------------------------