752 Open source projects that are alternatives of or similar to Machine Learning Uiuc

playing idealized trading games with deep reinforcement learning

Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks

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PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".

🎮 Advanced Deep Learning and Reinforcement Learning at UCL & DeepMind | YouTube videos 👉

Implementation of the Deep Q-learning algorithm to solve MDPs

An advanced program in Machine Learning and Deep Learning

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Resources, papers, tutorials

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

Pytorch implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning https://arxiv.org/abs/1705.04862

For deep RL and the future of AI.

A High Level Python Deep Reinforcement Learning library. Great for beginners, prototyping and quickly comparing algorithms

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Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

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Highly Modular and Scalable Reinforcement Learning

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

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Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.

PyTorch implementation of Soft Actor-Critic (SAC)

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Reinforcement Learning Algorithms

Reinforcement learning environments with musculoskeletal models

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

Using deep reinforcement learning to tackle the game 2048.

Solved lab problems, slides and notes of the Deep Reinforcement Learning bootcamp 2017 held at UCBerkeley

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Playing Atari games with TensorFlow implementation of Asynchronous Deep Q-Learning

Notes and comments about Deep Reinforcement Learning papers

PyTorch implementation of Deterministic Generative Adversarial Imitation Learning (GAIL) for Off Policy learning

MuZero

Artificial intelligence for the Snake game.

TensorFlow and Deep Learning Tutorials

Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...

My Solutions of Assignments of CS234: Reinforcement Learning Winter 2019

🤖 Implements of Reinforcement Learning algorithms.

PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

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PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments

A reinforcement learning package for Julia

My Solution to Assignments of CS234

Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

Unity Machine Learning Agents Toolkit

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Teach a Quadcopter How to Fly!

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Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

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A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).