Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/o-tawab/Github-Repositories

My collection of repositories that worth more care.
https://github.com/o-tawab/Github-Repositories

List: Github-Repositories

awesome computer-vision machine-learning nlp reinforcement-learning

Last synced: 3 months ago
JSON representation

My collection of repositories that worth more care.

Host: GitHub
URL: https://github.com/o-tawab/Github-Repositories
Owner: o-tawab
Created: 2017-03-05T20:16:51.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2017-03-31T20:06:07.000Z (over 7 years ago)
Last Synced: 2024-05-20T01:33:20.784Z (6 months ago)
Topics: awesome, computer-vision, machine-learning, nlp, reinforcement-learning
Size: 3.91 KB
Stars: 6
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

Github-Repositories - General
ultimate-awesome - Github-Repositories - My collection of repositories that worth more care. (Other Lists / PowerShell Lists)

README

        # Github-Repositories

My collection of repositories that worth more care.

##### [Markdown Cheatsheet](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet)

# Table of Contents

* [Machine Learning](https://github.com/3ammor/Github-Repositories#machine-learning)

  - [Computer Vision](https://github.com/3ammor/Github-Repositories#computer-vision)

    * Generative Adversarial Networks

    * Object Detection

  - [Reinforcement Learning](https://github.com/3ammor/Github-Repositories#reinforcement-learning)

    * Q-Learning

    * Policy Gradient

    * Model-Based

    * Others

  - [Natural Language Processing](https://github.com/3ammor/Github-Repositories#natural-language-processing)

  - [Courses](https://github.com/3ammor/Github-Repositories#courses)

    * Computer Vision

    * Reinforcement Learning

    * NLP

    * Others

  - [General](https://github.com/3ammor/Github-Repositories#general)

* [Awesome](https://github.com/3ammor/Github-Repositories#awesome)

  

***

## Machine Learning

### Computer Vision

##### Generative Adversarial Networks

  * [Deep Convolutional Generative Adversarial Networks](https://github.com/Newmu/dcgan_code)

  * [Pix2pix: Image-to-Image Translation with Conditional Adversarial Nets](https://github.com/affinelayer/pix2pix-tensorflow)

  * [Generative Adversarial Text-to-Image Synthesis](https://github.com/reedscot/icml2016)

  * [CycleGAN](https://github.com/junyanz/CycleGAN)

  

##### Object Detection

  * [TensorBox: Object detection in TensorFlow](https://github.com/TensorBox/TensorBox)

  * [Object Detection with Faster R-CNN in Chainer](https://github.com/mitmul/chainer-faster-rcnn)

  * [Tensorflow implementation of Faster R-CNN and ResNets](https://github.com/DeepRNN/object_detection)

### Reinforcement Learning

##### Q-Learning

  * [Implementation of prioritized experience replay](https://github.com/Damcy/prioritized-experience-replay)

  * [DQN-tensorflow](https://github.com/devsisters/DQN-tensorflow)

##### Policy Gradient

  * [Using Keras and Deep Deterministic Policy Gradient to play TORCS](https://github.com/yanpanlau/DDPG-Keras-Torcs)

  * [Asynchronous Methods for Deep Reinforcement Learning](https://github.com/miyosuda/async_deep_reinforce)

##### Model-Based

##### Others

  * [Magenta: Music and Art Generation with Machine Intelligence](https://github.com/tensorflow/magenta)

  * [Deep Reinforcement Learning Algorithms Implementation](https://github.com/only4hj/DeepRL)

  * [TensorFlow implementation of Deep Reinforcement Learning papers](https://github.com/carpedm20/deep-rl-tensorflow)

  * [A list of recent papers regarding deep reinforcement learning](https://github.com/junhyukoh/deep-reinforcement-learning-papers)

### Natural Language Processing

### Courses

##### Computer Vision

  * [class assingments CS231n](https://github.com/cthorey/CS231)

  

##### Reinforcement Learning

  * [Berkeley Deep RL Course Homework](https://github.com/berkeleydeeprlcourse/homework)

  * [Exercises and Solutions to accompany Sutton's Book and David Silver's course.](https://github.com/dennybritz/reinforcement-learning)

##### NLP

  * [Oxford Deep NLP 2017 course](https://github.com/oxford-cs-deepnlp-2017/lectures)

##### Others

  * [A complete computer science study plan to become a software engineer.](https://github.com/jwasham/coding-interview-university)

  * [Interviews](https://github.com/kdn251/interviews)

### General

  * [Summaries and notes on Deep Learning research papers](https://github.com/dennybritz/deeplearning-papernotes)

  

---

## Awesome

  * [awesome](https://github.com/sindresorhus/awesome)

  * [awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow)

  * [awesome-osx-command-line](https://github.com/herrbischoff/awesome-osx-command-line)

  * [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers)

  * [awesome-public-datasets](https://github.com/ChristosChristofidis/awesome-public-datasets)

  * [awesome-rl](https://github.com/aikorea/awesome-rl)

  * [awesome-rnn](https://github.com/kjw0612/awesome-rnn)

  * [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision)

  * [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning)