├── .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 | # Complete-Deep-Learning-with-Projects-Series- 2 | This repository contains everything you need to become proficient in Deep Learning 3 | 4 | Youtube for all the implemented projects and tech interview resources - [Ignito Youtube Channel](https://www.youtube.com/@ignito5917/about) 5 | 6 | [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) 7 | 8 | [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) 9 | 10 | [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) 11 | 12 | -------- 13 | 14 | # Neural Networks 15 | 16 | [Neural Networks basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 17 | 18 | [Different types of neural networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 19 | 20 | [Linear Classifiers](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 21 | 22 | [Optimization](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 23 | 24 | [Hyper Parameter Tuning](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 25 | 26 | [Gradient Descent](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 27 | 28 | [Backpropagation Algorithm](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 29 | 30 | [Regularization — L2 and dropout regularization](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 31 | 32 | [Batch normalization](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 33 | 34 | [Build a neural network in Keras](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 35 | 36 | [Build a Neural Network With Pytorch](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 37 | 38 | [Build a neural network in TensorFlow](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 39 | 40 | [Train Neural Networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 41 | 42 | [Feedforward neural network](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 43 | 44 | [Popular Optimization Algorithms](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 45 | 46 | [Activation Functions](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 47 | 48 | [Strategies for reducing errors](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 49 | 50 | [Shallow Neural Networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 51 | 52 | # Convolutional Neural Networks 53 | 54 | [Convolution basics and CNN Architectures](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 55 | 56 | [Residual networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 57 | 58 | [Build a Convolutional Network](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 59 | 60 | [Batch Normalization and Dropout](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 61 | 62 | # Recurrent Neural Networks 63 | 64 | [RNN Basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 65 | 66 | [LSTM: Long Short Term Memory Cells](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 67 | 68 | [Natural language processing and Word Embeddings](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 69 | 70 | # Tensorflow 71 | 72 | [Tensorflow basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 73 | 74 | [Tensorflow Playground](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 75 | 76 | [Custom Loss Functions](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 77 | 78 | [Custom Layers and Models](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 79 | 80 | [Callbacks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 81 | 82 | [Distributed Training](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 83 | 84 | [Data Pipelines with TensorFlow Data Services](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 85 | 86 | [Performance](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 87 | 88 | # Autoencoders 89 | 90 | [Autoencoders Basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 91 | 92 | [Generative Learning](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 93 | 94 | # Generative Adversarial Networks 95 | 96 | [Generative Adversarial Networks Basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 97 | 98 | [Useful activation functions and Batch normalization](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 99 | 100 | [Transposed convolutions](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 101 | 102 | [Generator and Discriminator](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 103 | 104 | [Deep Convolutional Generative Adversarial Networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 105 | 106 | [Implement Generative Adversarial Networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 107 | 108 | # Attention and Transformers 109 | 110 | [Attention and Transformers Basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 111 | 112 | [Sequence to Sequence Models](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 113 | 114 | [Attention](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 115 | 116 | [Multi-Head Self-Attention](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 117 | 118 | [Building Blocks of Transformers](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 119 | 120 | [Encoder](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 121 | 122 | [Decoder](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 123 | 124 | [Parameters Sharing](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 125 | 126 | [Build a Transformer Encoder](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 127 | 128 | # Graph Neural Networks 129 | 130 | [Basics of Graphs](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 131 | 132 | [Graph Convolutional Networks](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 133 | 134 | [Implement — Graph Convolutional Network](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 135 | 136 | # Natural Language Processing 137 | 138 | [Natural Language Processing Basics](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 139 | 140 | [Probabilistic Models](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 141 | 142 | [Sequence Models](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 143 | 144 | [Attention Models](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 145 | 146 | [Federated learning](https://medium.com/coders-mojo/implemented-deep-learning-projects-aa18d5551046?sk=ac0dacd3bce951bc2d63cf8fd30a6bde) 147 | --------------------------------------------------------------------------------