My blogs and code for machine learning. http://cnblogs.com/pinard
- machinelearning
- algorithms
- scikit-learn
- reinforcementlearning
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My blogs and code for machine learning. http://cnblogs.com/pinard
TranslatedBuild your neural network easy and fast, 莫烦Python (Morvan Python) Chinese teaching
Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.
Reading list for research topics in multimodal machine learning
A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.
🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.
A course in reinforcement learning in the wild
A curated list of awesome self-supervised methods
Implement a reasoning LLM in PyTorch from scratch, step by step
Repo for the Deep Reinforcement Learning Nanodegree program
This repo contains the Hugging Face Deep Reinforcement Learning Course.
Translated🌟100+ original LLM / RL algorithm diagrams📚, a great gift from the author of 《大模型算法》 (Large Model Algorithms)! 💥 (100+ LLM/RL Algorithm Maps)
Paper list of multi-agent reinforcement learning (MARL)
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Deep Reinforcement Learning
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
A curated list of reinforcement learning with human feedback resources (continually updated)
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Quantitative analysis, strategies and backtests
A curated list of awesome links and software libraries that are useful for robots.
👉 CARLA resources such as tutorial, blog, code and etc https://github.com/carla-simulator/carla
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning