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4,485 프로젝트
894스타
xquant-beginner preview

《XQuant:人人都是量化交易员》量化交易入门与自学开源书:用 AI 和 Python 从零跑通策略回测、风险评估、交易执行和因子研究。

학습TypeScriptGitHub
597스타

📚A curated list of Awesome Diffusion Inference Papers with Codes: Sampling, Cache, Quantization, Parallelism, etc.🎉

학습PythonGPL-3.0GitHub

NIID-Bench

Xtra-Computing

618스타

Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)

학습PythonMITGitHub
595스타

Learning Apache spark,including code and data .Most part can run local.

학습ScalaApache-2.0GitHub
26스타

学无止下载器|Windows 网课视频下载、课件 PDF/PPT 下载、直播回放保存、三分屏与板书课程处理。中国大学 MOOC、超星学习通、学堂在线、智慧树、网易云课堂、钉钉等平台图文教程;公开文档与 Python 离线骨架。

학습PythonMITGitHub

notears

xunzheng

695스타
notears preview

DAGs with NO TEARS: Continuous Optimization for Structure Learning

학습PythonApache-2.0GitHub

YaneuraOu

yaneurao

702스타

YaneuraOu is the World's Strongest Shogi engine(AI player) , WCSC29 1st winner , educational and USI compliant engine.

학습C++GPL-3.0GitHub

learning-rust

yangwenmai

588스타

Rust 学习之路 > Rust Programming Tutorial, include articles, interview, example, problems.

python

yazbel

558스타

YazBel Python Belgeleri; En kapsamlı ve ayrıntılı Türkçe Python belgelendirmesi

230스타
ai_beginner_guide preview

普通人看的 AI 入门。从零开始,掌握人工智能的最新工具与实践技能 | AI Book for Beginners

867스타

Awesome Kubestronaut. Resources to prepare for CKA, CKAD, CKS, KCNA, KCSA, PCA, ICA, CNPE, CNPA, CGOA, CAPA, KCA, BCA, OTCA, CCA

981스타

Awesome Sphinxdoc is a curated collection of valuable resources for Sphinx

  • Multi-language support (EN, KO, JA, ZH) with URL persistence (?lang=).
  • Tag-based filtering with URL persistence (?tag=).

DFT

yongliang-wu

928스타

[ICLR 2026] On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification.

568스타

RLGF is a general training framework suitable for UAV deep reinforcement learning tasks. And integrates multiple mainstream deep reinforcement learning algorithms(SAC, DQN, DDQN, PPO, Dueling DQN, DDPG).

학습PythonMITGitHub

PAL

YuChuang1205

589스타

[🔥Accepted by ICCV2025🔥] Official code of the paper "From Easy to Hard: Progressive Active Learning Framework for Infrared Small Target Detection with Single Point Supervision"