Deeprl TutorialsContains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
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RadRAD: Reinforcement Learning with Augmented Data
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Lagomlagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
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BtgymScalable, event-driven, deep-learning-friendly backtesting library
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Accel Brain CodeThe 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.
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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
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MultihopkgMulti-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout
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Applied Reinforcement LearningReinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks
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Openai labAn experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.
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DrqDrQ: Data regularized Q
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Deep Q LearningMinimal Deep Q Learning (DQN & DDQN) implementations in Keras
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Deep AlgotradingA resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
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TrpoTrust Region Policy Optimization with TensorFlow and OpenAI Gym
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Pytorch RlThis repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
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Rl BookSource codes for the book "Reinforcement Learning: Theory and Python Implementation"
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TorchrlHighly Modular and Scalable Reinforcement Learning
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Slm LabModular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
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CurlCURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
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Amazon Sagemaker ExamplesExample 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
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DeepdriveDeepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
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ElegantrlLightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch.
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TraxTrax — Deep Learning with Clear Code and Speed
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