# stanford-cs-230-deep-learning

**Repository Path**: limbercode/stanford-cs-230-deep-learning

## Basic Information

- **Project Name**: stanford-cs-230-deep-learning
- **Description**: VIP cheatsheets for Stanford's CS 230 Deep Learning
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-02-08
- **Last Updated**: 2022-02-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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)