A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.

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Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

The Arcade Learning Environment (ALE) -- a platform for AI research.

Emulate a conventional USB keyboard with a scriptable, network capable microcontroller.

Deep and online learning with spiking neural networks in Python

EEEA-Net: An Early Exit Evolutionary Neural Architecture Search

A Tutorial on Neural Networks and Activation Functions

Simple A3C implementation with pytorch + multiprocessing

Build-related tools for TensorFlow

DQN Zoo is a collection of reference implementations of reinforcement learning agents developed at DeepMind based on the Deep Q-Network (DQN) agent.

Free hands-on course about Graph Neural Networks using PyTorch Geometric.

Official Python code implementation of CLRS-4th-Edition

Hands-on tutorial on Bayesian optimization for learning rate optimization on the K-MNIST dataset using PyTorch.

[CVPR2020] CARS: Continuous Evolution for Efficient Neural Architecture Search

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

Azure IoT Edge

Computation using data flow graphs for scalable machine learning

All the Git-it Workshop completers!

This repo is for demonstration purposes only. Comments and issues may or may not be responded to.