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https://github.com/toxtli/awesome-machine-learning-jupyter-notebooks-for-colab

A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory
https://github.com/toxtli/awesome-machine-learning-jupyter-notebooks-for-colab

List: awesome-machine-learning-jupyter-notebooks-for-colab

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A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory

Host: GitHub
URL: https://github.com/toxtli/awesome-machine-learning-jupyter-notebooks-for-colab
Owner: toxtli
Created: 2019-10-14T01:50:30.000Z (about 5 years ago)
Default Branch: master
Last Pushed: 2019-10-15T21:23:20.000Z (about 5 years ago)
Last Synced: 2024-05-23T07:20:23.003Z (5 months ago)
Topics: awesome, awesome-list, awesome-lists, deep-learning, jupyter-notebook, jupyter-notebooks, machine-learning
Language: Jupyter Notebook
Homepage: http://www.carlostoxtli.com/#colab-awesome
Size: 83 KB
Stars: 278
Watchers: 11
Forks: 69
Open Issues: 0
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

ultimate-awesome - awesome-machine-learning-jupyter-notebooks-for-colab - A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory. (Other Lists / PowerShell Lists)

README

        [![Logo](awesome.png)](https://www.carlostoxtli.com/#awesome)

# Awesome Machine Learning Jupyter Notebooks for Google Colaboratory [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

> A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory

You can find the credits for the authors in the header of each Jupyter Notebook.

## Contents

- [Machine Learning](#machine-learning)

- [Deep Learning](#deep-learning)

- [Reinforcement Learning](#reinforcement-learning)

## Machine Learning

- [Supervised Learning plots](https://www.google.com/url?q=https://colab.research.google.com/drive/1gmZWE7Tynhx1g9vzeqyaMPdO0pdwLmuJ&sa=D&ust=1571021489211000)

- [Unsupervised Learning plots](https://www.google.com/url?q=https://colab.research.google.com/drive/1yWT08sgqswCkuZx06EH3qdZcWTPp2Wvt&sa=D&ust=1571021489212000)

- [Machine Learning Basic concepts 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1ZgDgOcb4NR-u62cFMdZJBPXux95E4wZt&sa=D&ust=1571021489213000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/12X03Yz5Om_ryN9FnuhLvgMe8khB7RUC5&sa=D&ust=1571021489213000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1ldHvgs9qeNIWBCxT0U8OT9SkSisVd4sj&sa=D&ust=1571021489213000) & [4](https://www.google.com/url?q=https://colab.research.google.com/drive/1_6gJHuKOc2-cCLXsNhZ7DW89nF_G1NP-&sa=D&ust=1571021489213000)

- [Linear Regression 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1-dTb2vCiZHa-DnyqlVFGOnMSNjvkIOTP&sa=D&ust=1571021489214000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1Z20iJspQm2Y_wLI51wgE6nXGOSu1kG4W&sa=D&ust=1571021489214000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1-yk3m6p3ylNLtTaEf3nya6exO_wv8f_L&sa=D&ust=1571021489214000)

- [Decision Trees 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1Fc8qs1fwdcpoZ_-tTj32OBl-tCGlAe5c&sa=D&ust=1571021489215000)

- [Random Forest 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1WMOOtaHAMZPi-enVM8RRM_CC-grEtm9P&sa=D&ust=1571021489215000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1jDdWp-CJybMJDX17jBmG5qoPPg9qj1sm&sa=D&ust=1571021489215000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1-uDIRl1aYqmJX59rAJumHY1T20QqBJiQ&sa=D&ust=1571021489216000) & [4](https://www.google.com/url?q=https://colab.research.google.com/drive/1-uDIRl1aYqmJX59rAJumHY1T20QqBJiQ&sa=D&ust=1571021489216000)

- [Naive Bayes 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1qOCllKsBBrLeUnP-XAXHefXCtbuBWl69&sa=D&ust=1571021489216000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/11FiWH00vzygQp1T_pD0MCfMFg6FYsd01&sa=D&ust=1571021489217000)

- [k-Nearest Neighbor 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1GeUVjDW74SxFxz2Nh3rqOlte-S2dblYv&sa=D&ust=1571021489217000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1X12qds10ZfN7QCrmpRR2OXxa--PTyS5e&sa=D&ust=1571021489218000)

- [k-Means 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1RL3oZm6LgnEChI1aOQZoMn1WDk-DQJiV&sa=D&ust=1571021489218000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1yvy1scktjcDyydG2fZz2OJfRFAer0SEO&sa=D&ust=1571021489218000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1CzEf6giBXPSQI5UJOhZrZfYKAJcH68wg&sa=D&ust=1571021489218000)

- [Support Vector Machines 1](https://www.google.com/url?q=https://colab.research.google.com/drive/13PRk-GKeSivp4R-FIdjmYBQS7xWUco9C&sa=D&ust=1571021489219000)

- [Logistic Regression 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1PWmvsZRaj3JQ8rtj6vlwhJhJpOrIAamT&sa=D&ust=1571021489219000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1p8rcrSQB-thLSakUmCHjSbqI6vd-NkCq&sa=D&ust=1571021489220000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1jhrAtmPgg6Uu0WzMzV-VakWlncQAvk-D&sa=D&ust=1571021489220000)

- [Perceptron 1](https://www.google.com/url?q=https://colab.research.google.com/drive/10PvUh-8ZsVqQADqXSmRIDHGiCH9iypyO&sa=D&ust=1571021489220000)

- [Machine Learning Overview 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1s6cBKRS-M0NUtgGhMtbJvGV_H5Zusw3w&sa=D&ust=1571021489220000)

- [Principal Component Analysis 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1CO6BACds6J8hGPYlEU2INnSTpT0EmS74&sa=D&ust=1571021489221000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1VU2SO3IfklPkK1EPMnwiO7trJslt79OZ&sa=D&ust=1571021489221000)

- [Topic modeling 1](https://www.google.com/url?q=https://colab.research.google.com/drive/12O3tgKY_6uppbEVL1PzGRfbo7w69RLQu&sa=D&ust=1571021489221000)

- [Ensembles 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1Kg_nHBmUGQ1zepU-wZlDwMyM-YrlMTUX&sa=D&ust=1571021489233000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1U86EVD-6ulYMxTzDX8-m6nEptYq0yaej&sa=D&ust=1571021489233000)

## Deep Learning

- [GPU testing 1](https://www.google.com/url?q=https://colab.research.google.com/drive/17vJw-LAGhA6OT8KGar8h22NY4STruCSq&sa=D&ust=1571021489222000)

- [Artificial Neural Networks from scratch 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1Vfz7XMI9oubrsQSwN3ZbMC6ph_rJJK_C&sa=D&ust=1571021489222000)

- [ANN Activation functions 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1XQHKjJJs7pWsqCenAiLPx8Y-JnqQrO48&sa=D&ust=1571021489223000)

- [ANN Loss functions 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1YHa7WNP_2hwStfV0CQFJI9SgZIxX4YbB&sa=D&ust=1571021489223000)

- [ANN Gradients 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1xQ1TdpeaLCYnagl_R2C8_ilRl2J-nYO0&sa=D&ust=1571021489223000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1FSepBy85HBrHa8t8aoxY5HKuz4sJ4CAo&sa=D&ust=1571021489223000)

- [ANN Optimizers 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1i4JZOghgXSf98ty2wybcTHm4FkRsJMyM&sa=D&ust=1571021489224000)

- [ANN Decision Boundaries 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1s9Sk2bf7QjNxgiilprauXNCigvmG3Rd8&sa=D&ust=1571021489224000)

- [ANN Overfitting 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1wFUEfNhy3az_hMS5EWZK7c7frpzS5X_N&sa=D&ust=1571021489224000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1QBEtDv70bBYchu2508OJYC_0d_XVrUaD&sa=D&ust=1571021489225000)

- [ANN Regularization 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1Scpx9rb800-hVhjF-F-E8YeTPWTIyQAq&sa=D&ust=1571021489225000)

- [Multi-Layer Perceptron 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1GAYf5yMNBkVrag0z2Q4MPSwuqfRN1Wz_%23scrollTo%3Ds4VYW0i94W_n&sa=D&ust=1571021489225000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/12YBDQFYXN8VruxKTfzDpbPsYFAEQceQP&sa=D&ust=1571021489226000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1pyRqGmMG4-Mj8Wis5XrQ_a4dUJvYln1g&sa=D&ust=1571021489226000) & [4](https://www.google.com/url?q=https://colab.research.google.com/drive/1wHjugM56k0ay5QCmRVMBfAMF96EY7A5k&sa=D&ust=1571021489226000) & [5](https://www.google.com/url?q=https://colab.research.google.com/drive/1Ly0BtKBphUdeqMQBO8Xjweku62Vq3UAX&sa=D&ust=1571021489226000)

- [Convolutional Neural Networks 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1jN8oswBOds4XuRbnQMxxDXDssmDD_rD9&sa=D&ust=1571021489227000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1iEYJs75hat_URxshmCBMGzHQo5VgdRvN%23scrollTo%3DQ4UZVi3DYqbr&sa=D&ust=1571021489227000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1YHKZgpJuriGYjEzFDNGz2Hf0widu-exx&sa=D&ust=1571021489227000) & [4](https://www.google.com/url?q=https://colab.research.google.com/drive/1gi2_Or0rDz5Gg9FkGJjFDxgeiwt5-lXm&sa=D&ust=1571021489227000) & [5](https://www.google.com/url?q=https://colab.research.google.com/drive/1QcnY-LOZU9c7Sp2DsDVeYxLNBx87VNhn&sa=D&ust=1571021489228000) & [6](https://www.google.com/url?q=https://colab.research.google.com/drive/1Il7eimZ5bxQh1qem-NLiwoMBugODltSI&sa=D&ust=1571021489228000) & [7](https://www.google.com/url?q=https://colab.research.google.com/drive/1YHKZgpJuriGYjEzFDNGz2Hf0widu-exx&sa=D&ust=1571021489228000) & [8](https://www.google.com/url?q=https://colab.research.google.com/drive/1iEYJs75hat_URxshmCBMGzHQo5VgdRvN&sa=D&ust=1571021489229000) & [9](https://www.google.com/url?q=https://colab.research.google.com/drive/1w9GxDTBATF6Cc_1582V6uU2OKdQGnp0J&sa=D&ust=1571021489229000)

- [CNN from scratch 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1RqD0OMGFcKBiVIyZIr1qfvM-edWLPY64&sa=D&ust=1571021489229000)

- [Data Augmentation 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1ANIc7tXrggPT2I9JzpBlZQ3BBhCpbJUJ&sa=D&ust=1571021489230000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1cQRVdiDc9xraHZYLu3VrXxX4FKXoaS8U&sa=D&ust=1571021489230000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1O5far2FC4GlAc9pkLPZqsjKreCpI4S_-&sa=D&ust=1571021489230000)

- [Recurrent Neural Networks 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1twc5dBjgFLFuv8p-gPfnrscTPcBlkx5q&sa=D&ust=1571021489231000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/10-ou-Za75bFgwArvgP3QfNJ4cWuwY-eF&sa=D&ust=1571021489231000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1PEOqq8mBcmc-FMj8lpbVF93cQI4RLgVJ&sa=D&ust=1571021489231000) & [4](https://www.google.com/url?q=https://colab.research.google.com/drive/1XUEAFxxKVmdgC7oPOzVpGInXfUeTcgIQ&sa=D&ust=1571021489231000) & [5](https://www.google.com/url?q=https://colab.research.google.com/drive/1tfDDriSDUh_J9OHwjt-NzT8xRiEDQF7x&sa=D&ust=1571021489232000)

- [Autoencoders 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1QxXqnhyqIZrrGtor2tVa4jY63adS4yc0&sa=D&ust=1571021489232000)

- [Generative Adversarial Networks 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1YOYH78YQAgPBRIpUPhh_e0cFLNu-BPVo&sa=D&ust=1571021489232000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/1POZpWN-2M5hy3D2ATWzJs2LC5sk7hpts&sa=D&ust=1571021489232000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1aKywiJ5p0eCwDIIWKe8Q205rcKqmR_VX&sa=D&ust=1571021489233000) & [4](https://www.google.com/url?q=https://colab.research.google.com/drive/1QxXqnhyqIZrrGtor2tVa4jY63adS4yc0&sa=D&ust=1571021489233000) & [5](https://www.google.com/url?q=https://colab.research.google.com/drive/1Lw7BqKABvtiSyUHg9DeM5f90_WFGB7uz&sa=D&ust=1571021489233000)

- [AutoML 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1gTBDfbJy9SsgbUPRhL_mrujw6HC2BjxN&sa=D&ust=1571021489234000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/17Ii6Nw89gZT8l_XrvSQhNWaa_VfcdLBn&sa=D&ust=1571021489234000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/1xe4G_dqsPMq0n3w_Mqlm-39j5TMUqHJR&sa=D&ust=1571021489234000)

## Reinforcement Learning

- [Reinforcement Learning 1](https://www.google.com/url?q=https://colab.research.google.com/drive/1fgv5UWhHR7xSwZfwwltF4OFDYqtWdlQD&sa=D&ust=1571021489235000) & [2](https://www.google.com/url?q=https://colab.research.google.com/drive/14aYmND2LKtaPTW3JWS7scKGwU9baxHeE&sa=D&ust=1571021489235000) & [3](https://www.google.com/url?q=https://colab.research.google.com/drive/16Scl43smvcXGZFEGITs15_SN_7-EidZd&sa=D&ust=1571021489235000)

## Contribute

Contributions welcome! Read the [contribution guidelines](CONTRIBUTING.md) first.

## License

[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](http://creativecommons.org/publicdomain/zero/1.0)