shibihe Goto Github PK

active_learning_version1

async-rl

Replicating "Asynchronous Methods for Deep Reinforcement Learning" (http://arxiv.org/abs/1602.01783)

atfm_bpr

Bayesian Personalized Ranking Model with Attribute-to-Feature Mappings for Cold-Start Recommendation

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

cvpr2015

deep_q_rl

Theano-based implementation of Deep Q-learning

deepmind-atari-deep-q-learner

The original code from the DeepMind article + my tweaks

doubanmoviesearch

dqn

This is a very basic DQN implementation, which uses OpenAI's gym environment and Keras/Theano neural networks.

dqn-multigpus

dqn_openai_keras

This is the DQN implementation written by myself using OpenAI gym and keras.

gym

A toolkit for developing and comparing reinforcement learning algorithms.

machine-learning-classifying-emails-into-spams-and-hams

Naive Bayes and Logistic Regression

machine_learning_deng_cai

Deng Cai's ML course

mixmhc

model-free-episodic-control

This is the implementation of paper Model Free Episodic Control

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

paper-notes

Some notes of papers I have read

poker-fictitious-play

Fictitious Self-play & Reinforcement Learning

q-optimality-tightening

This is my implementation of the Optimality Tightening

reinforcement-learning-an-introduction

Python code for Reinforcement Learning: An Introduction

shibihe.github.io

stanford-cs231n-assignments

The assignments of CS231n finished by me

stanford_dl_ex

Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial

tensorflow

Computation using data flow graphs for scalable machine learning

webgl-lessons

https://github.com/tparisi/webgl-lessons is now the officially maintained fork for this project

wedream-android