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machine-learning GitHub repositories

Explore 621 tracked GitHub repositories tagged machine-learning. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-28. The collection gained 3,160 stars since the previous daily snapshot.

Tracked repositories
621
Total stars
5,136,863
Stars gained · 7 days
+21,503
Stars gained · 30 days
+76,523

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Star activity for machine-learning repositories on this page
RepositoryTotal starsToday7 days30 days
WeThinkIn/AIGC-Interview-Book5.1K+8+56+250
sktime/pytorch-forecasting5.0K+0+1+6
Nixtla/statsforecast5.0K+3+9+35
alvinreal/awesome-opensource-ai4.9K+3+29+149
dusty-nv/jetson-containers4.9K+1+3+44

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Showing 201–250 of 621 tracked repositories.

WeThinkIn/AIGC-Interview-Book

【三年面试五年模拟】AIGC/LLM/AI Agent算法工程师面试资源平台。涵盖AIGC、LLM大模型、AI Agent、具身智能、传统深度学习、计算机视觉、自然语言处理、自动驾驶、机器学习、强化学习、大数据挖掘、世界模型、元宇宙、AGI等AI行业面试笔试干货经验与核心跨周期知识。

py-why/EconML

ALICE (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.

TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.