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Deep learning paper implementations with side-by-side notes and explanations
A comprehensive Chinese tutorial on reinforcement learning, with implementations of popular RL algorithms.
An elegant PyTorch deep reinforcement learning library for vibe coders building AI-powered applications.
Simple reinforcement learning tutorials in Python using TensorFlow for AI/ML developers.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features.
A comprehensive PyTorch tutorial for building neural networks and AI models with ease
A deep learning and reinforcement learning library for scientists and engineers, with support for TensorFlow.
This is a repository for the Udacity Deep Reinforcement Learning Nanodegree program, focusing on deep reinforcement learning algorithms and techniques.
A comprehensive resource for learning deep reinforcement learning with Python and Jupyter Notebook.
A comprehensive TensorFlow tutorial covering a wide range of machine learning topics for AI-focused developers.
Massively parallel deep reinforcement learning library for efficient, stable, and lightweight RL models.
A minimalist and clean set of reinforcement learning examples in Python for developers to learn and experiment with.
A comprehensive collection of deep learning resources including courses, case studies, and interview questions.
Modularized implementation of deep reinforcement learning algorithms in PyTorch for researchers and developers.
Clean, robust, and unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms.
Pytorch implementation of various deep reinforcement learning algorithms for vibe coders.
Minimal implementations of basic reinforcement learning algorithms in PyTorch for educational purposes.
A scalable and easy-to-use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Implementation of Deep Q-Learning in TensorFlow for building AI agents that can learn to play games.
An OpenAI Gym-based trading environment for developing and testing AI-driven trading algorithms.
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