6,582 skills found · Page 1 of 220
openai / GymA toolkit for developing and comparing reinforcement learning algorithms.
TheAlgorithms / C Plus PlusCollection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
eriklindernoren / ML From ScratchMachine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
trekhleb / Homemade Machine Learning🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
dennybritz / Reinforcement LearningImplementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
TheAlgorithms / CCollection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
lightgbm-org / LightGBMA fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
stefan-jansen / Machine Learning For TradingCode for Machine Learning for Algorithmic Trading, 2nd edition.
openai / BaselinesOpenAI Baselines: high-quality implementations of reinforcement learning algorithms
DLR-RM / Stable Baselines3PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
tangyudi / AI Learn人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
rushter / MLAlgorithmsMinimal and clean examples of machine learning algorithms implementations
google / DopamineDopamine is a research framework for fast prototyping of reinforcement learning algorithms.
vwxyzjn / CleanrlHigh-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
PRML / PRMLTMatlab code of machine learning algorithms in book PRML
p-christ / Deep Reinforcement Learning Algorithms With PyTorchPyTorch implementations of deep reinforcement learning algorithms and environments
uber / CausalmlUplift modeling and causal inference with machine learning algorithms
google-deepmind / Open SpielOpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Nyandwi / Machine Learning CompleteA comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
py-why / EconMLALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
