Practical dlDL course co-developed by YSDA, HSE and Skoltech
Stars: ✭ 1,006 (-78.78%)
GdrlGrokking Deep Reinforcement Learning
Stars: ✭ 304 (-93.59%)
RadRAD: Reinforcement Learning with Augmented Data
Stars: ✭ 268 (-94.35%)
Reinforcement LearningLearn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Stars: ✭ 3,329 (-29.78%)
DrqDrQ: Data regularized Q
Stars: ✭ 268 (-94.35%)
AgentnetDeep Reinforcement Learning library for humans
Stars: ✭ 298 (-93.71%)
Reinforcement learning tutorial with demoReinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
Stars: ✭ 442 (-90.68%)
Pytorch RlTutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
Stars: ✭ 121 (-97.45%)
Deeprl TutorialsContains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Stars: ✭ 748 (-84.22%)
Deeplearning2020course materials for introduction to deep learning 2020
Stars: ✭ 90 (-98.1%)
Lagomlagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
Stars: ✭ 364 (-92.32%)
Applied Reinforcement LearningReinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks
Stars: ✭ 229 (-95.17%)
Rl BookSource codes for the book "Reinforcement Learning: Theory and Python Implementation"
Stars: ✭ 464 (-90.21%)
Rl QuadcopterTeach a Quadcopter How to Fly!
Stars: ✭ 124 (-97.38%)
Reinforcementlearning AtarigamePytorch 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
Stars: ✭ 118 (-97.51%)
Alphazero gomokuAn implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
Stars: ✭ 2,570 (-45.79%)
Deep Learning PythonIntro to Deep Learning, including recurrent, convolution, and feed forward neural networks.
Stars: ✭ 94 (-98.02%)
PsganPeriodic Spatial Generative Adversarial Networks
Stars: ✭ 108 (-97.72%)
Pytorch sacPyTorch implementation of Soft Actor-Critic (SAC)
Stars: ✭ 174 (-96.33%)
BtgymScalable, event-driven, deep-learning-friendly backtesting library
Stars: ✭ 765 (-83.86%)
RlgraphRLgraph: Modular computation graphs for deep reinforcement learning
Stars: ✭ 272 (-94.26%)
Pytorch Image ClassificationTutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
Stars: ✭ 272 (-94.26%)
Popular Rl AlgorithmsPyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
Stars: ✭ 266 (-94.39%)
Prometheus Anomaly DetectorA newer more updated version of the prometheus anomaly detector (https://github.com/AICoE/prometheus-anomaly-detector-legacy)
Stars: ✭ 273 (-94.24%)
RlquantApplying Reinforcement Learning in Quantitative Trading
Stars: ✭ 271 (-94.28%)
TensorforceTensorforce: a TensorFlow library for applied reinforcement learning
Stars: ✭ 3,062 (-35.41%)
DinoruntutorialAccompanying code for Paperspace tutorial "Build an AI to play Dino Run"
Stars: ✭ 285 (-93.99%)
Deep rlPyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, SAC-AEA)
Stars: ✭ 291 (-93.86%)
Trading BotStock Trading Bot using Deep Q-Learning
Stars: ✭ 273 (-94.24%)
TensorwatchDebugging, monitoring and visualization for Python Machine Learning and Data Science
Stars: ✭ 3,191 (-32.69%)
IntrotodeeplearningLab Materials for MIT 6.S191: Introduction to Deep Learning
Stars: ✭ 4,955 (+4.51%)
Neural Symbolic MachinesNeural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.
Stars: ✭ 305 (-93.57%)
Reward Learning Rl[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering
Stars: ✭ 310 (-93.46%)
Pytorch TrpoPyTorch implementation of Trust Region Policy Optimization
Stars: ✭ 303 (-93.61%)
A3c tradingTrading with recurrent actor-critic reinforcement learning
Stars: ✭ 305 (-93.57%)
Openai labAn experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.
Stars: ✭ 313 (-93.4%)
Deeprl Tensorflow2🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Stars: ✭ 319 (-93.27%)
LearningThe data is the future of oil, digging the potential value of the data is very meaningful. This library records my road of machine learning study.
Stars: ✭ 330 (-93.04%)
RlzooA Comprehensive Reinforcement Learning Zoo for Simple Usage 🚀
Stars: ✭ 342 (-92.79%)
QuantumkatasTutorials and programming exercises for learning Q# and quantum computing
Stars: ✭ 3,713 (-21.68%)
TrpoTrust Region Policy Optimization with TensorFlow and OpenAI Gym
Stars: ✭ 343 (-92.77%)
Meta RlImplementation of Meta-RL A3C algorithm
Stars: ✭ 355 (-92.51%)
Tf2rlTensorFlow2 Reinforcement Learning
Stars: ✭ 353 (-92.55%)
GenrlA PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL
Stars: ✭ 356 (-92.49%)
CurlCURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
Stars: ✭ 346 (-92.7%)
QtraderReinforcement Learning for Portfolio Management
Stars: ✭ 363 (-92.34%)
Starcraft Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
Stars: ✭ 372 (-92.15%)