Reinforcement Learning
Showing 36 of 86 projects
A customizable 3D platform based on Quake III for agent-based AI and deep reinforcement learning research.
A Python framework for creating AI agents that learn to play any video game you own.
An open course on reinforcement learning with a practical focus, featuring hands-on labs and comprehensive materials for both online and on-campus students.
An open course on reinforcement learning with a practical focus, featuring hands-on labs and comprehensive materials for both online and on-campus students.
A high-performance neural network training interface for TensorFlow focused on speed, flexibility, and reproducible research.
A high-performance neural network training interface for TensorFlow, optimized for speed and research flexibility.
An open-source Python framework for building, training, and evaluating reinforcement learning agents for algorithmic trading.
A curated list of awesome resources for applying LLMs and deep learning to financial market analysis and algorithmic trading.
An open-source Go engine that replicates AlphaGo Zero's architecture, learning solely through self-play without human knowledge.
A complete AI-driven process using GANs with LSTM and CNN to predict stock price movements, incorporating diverse data sources and hyperparameter optimization.
A Python library implementing state-of-the-art deep reinforcement learning algorithms with seamless Keras integration.
An open-source pipeline for training medical domain GPT models using PT, SFT, RLHF, DPO, ORPO, and GRPO methods.
A high-performance Game Boy emulator written in Python, designed for AI training, game automation, and classic gameplay.
Official code repository for the 'Machine Learning with TensorFlow' book with practical examples.
An AI experimentation platform built on Minecraft for training and researching intelligent agents in complex 3D environments.
A research framework for reinforcement learning providing modular building blocks and reference agent implementations.
An open-source platform for building, training, and monitoring large-scale deep learning applications with full lifecycle MLOps.
An end-to-end platform for applied reinforcement learning and contextual bandits, built with PyTorch for production decision-making systems.
An end-to-end platform for applied reinforcement learning and contextual bandits, originally developed at Facebook for production recommendation systems.
A collection of handwritten notes, notebooks, and resources for Andrew Ng's Deep Learning Specialization on Coursera.
A comprehensive Python-first reinforcement learning framework with modular abstractions for decision intelligence applications.
A curated collection of high-quality resources for quantitative and algorithmic trading with a focus on machine learning applications.
A toolkit for turning classic video games into Gym environments for reinforcement learning research.
A debugging and visualization tool for data science, deep learning, and reinforcement learning in Jupyter Notebook.
A Python library providing a standardized API for multi-agent reinforcement learning environments with diverse reference games.
A PyTorch framework for deep learning research and development, focusing on reproducibility and rapid experimentation.
A modular TensorFlow library for applied reinforcement learning with a focus on flexible design and practical usability.
A modular TensorFlow library for applied reinforcement learning with a focus on flexible design and practical usability.
A collection of minimalist Gymnasium environments for autonomous driving decision-making and reinforcement learning research.
A TensorFlow library providing building blocks for implementing Reinforcement Learning agents.
A fast, differentiable physics engine built with JAX for massively parallel rigid body simulation on accelerator hardware.
An AI-native modular infrastructure for quantitative trading, featuring a weight-centric architecture for building, testing, and deploying algorithmic strategies.
A TensorFlow library for implementing, deploying, and testing Contextual Bandits and Reinforcement Learning algorithms.
A collection of Python notebooks and tools for quantitative finance research, including backtesting, machine learning, and portfolio optimization.
A curated list of robotics libraries, simulators, and software for developers and researchers.
A JAX-native library implementing Monte Carlo tree search algorithms like AlphaZero and MuZero for reinforcement learning research.
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