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Professional software vendor delivering innovative solutions on the Softono platform. Specialized in both open-source and proprietary software development.

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2

Software by afshinea

stanford-cs-229-machine-learning
Open Source

stanford-cs-229-machine-learning

# Machine Learning cheatsheets for Stanford's CS 229 Available in [العربية](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/ar) - [English](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/en) - [Español](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/es) - [فارسی](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/fr) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks) - [Português](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/pt) - [Türkçe](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/vi) - [简中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh) - [繁中](https://github.com/afshinea/stanford-cs-229-machine-learning/tree/master/zh-tw) ## Goal This repository aims at summing up in the same place all the important notions that are covered in Stanford's CS 229 Machine Learning course, and include: - **Refreshers** in related topics that highlight the key points of the **prerequisites of the course**. - **Cheatsheets for each machine learning field**, as well as another dedicated to tips and tricks to have in mind when training a model. - All elements of the above combined in an **ultimate compilation of concepts**, to have with you at all times! ## Content #### VIP Cheatsheets |<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-001.png?" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-002.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-003.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-004.png" alt="Illustration" width="220px"/></a>| |:--:|:--:|:--:|:--:| |Supervised Learning|Unsupervised Learning|Deep Learning|Tips and tricks| #### VIP Refreshers |<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-005.png" alt="Illustration" width="220px"/></a>|<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-006.png#1" alt="Illustration" width="220px"/></a>| |:--:|:--:| |Probabilities and Statistics|Algebra and Calculus| #### Super VIP Cheatsheet |<a href="https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-229/illustrations/cover/en-007.png" alt="Illustration" width="400px"/></a>| |:--:| |All the above gathered in one place| ## Website This material is also available on a dedicated [website](https://stanford.edu/~shervine/teaching/cs-229), so that you can enjoy reading it from any device. ## Translation Would you like to see these cheatsheets in your native language? You can help us translating them on [this dedicated repo](https://github.com/shervinea/cheatsheet-translation)! ## Authors [Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) and [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)

Education & Learning ML Frameworks
19.5K Github Stars
stanford-cs-230-deep-learning
Open Source

stanford-cs-230-deep-learning

# Deep Learning cheatsheets for Stanford's CS 230 Available in [English](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/en) - [فارسی](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fa) - [Français](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/fr) - [日本語](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/ja) - [한국어](https://stanford.edu/~shervine/l/ko/teaching/cs-230/cheatsheet-convolutional-neural-networks) - [Türkçe](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/tr) - [Tiếng Việt](https://github.com/afshinea/stanford-cs-230-deep-learning/tree/master/vi) ## Goal This repository aims at summing up in the same place all the important notions that are covered in Stanford's CS 230 Deep Learning course, and include: - **Cheatsheets detailing everything** about convolutional neural networks, recurrent neural networks, as well as the tips and tricks to have in mind when training a deep learning model. - All elements of the above combined in an **ultimate compilation of concepts**, to have with you at all times! ## Content #### VIP Cheatsheets |<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-convolutional-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-001.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-recurrent-neural-networks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-002.png?" alt="Illustration" width="280px"/></a>|<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-deep-learning-tips-tricks.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-003.png?" alt="Illustration" width="280px"/></a>| |:--:|:--:|:--:| |Convolutional Neural Networks|Recurrent Neural Networks|Tips and tricks| #### Super VIP Cheatsheet |<a href="https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/super-cheatsheet-deep-learning.pdf"><img src="https://stanford.edu/~shervine/teaching/cs-230/illustrations/cover/en-004.png?" alt="Illustration" width="400px"/></a>| |:--:| |All the above gathered in one place| ## Website This material is also available on a dedicated [website](https://stanford.edu/~shervine/teaching/cs-230), so that you can enjoy reading it from any device. ## Translation Would you like to see these cheatsheets in your native language? You can help us translating them on [this dedicated repo](https://github.com/shervinea/cheatsheet-translation)! ## Authors [Afshine Amidi](https://twitter.com/afshinea) (Ecole Centrale Paris, MIT) and [Shervine Amidi](https://twitter.com/shervinea) (Ecole Centrale Paris, Stanford University)

Education & Learning ML Frameworks
7K Github Stars