Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Cheatsheets Ai | 13,281 | 5 years ago | 6 | mit | ||||||
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5 | ||||||||||
Abu | 10,540 | 7 months ago | 2 | gpl-3.0 | Python | |||||
阿布量化交易系统(股票,期权,期货,比特币,机器学习) 基于python的开源量化交易,量化投资架构 | ||||||||||
Ai Learn | 8,256 | 4 months ago | 20 | |||||||
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 | ||||||||||
Datasets | 4,094 | 51 | 163 | 4 months ago | 36 | September 08, 2023 | 653 | apache-2.0 | Python | |
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ... | ||||||||||
Machine Learning With Python | 2,980 | a year ago | 8 | bsd-2-clause | Jupyter Notebook | |||||
Practice and tutorial-style notebooks covering wide variety of machine learning techniques | ||||||||||
Projectlearn Project Based Learning | 2,074 | 6 months ago | 4 | mit | JavaScript | |||||
A curated list of project tutorials for project-based learning. | ||||||||||
Machine_learning_beginner | 1,594 | 3 years ago | Jupyter Notebook | |||||||
机器学习初学者公众号作品 | ||||||||||
Machine_learning_refined | 1,574 | 10 months ago | 1 | other | Python | |||||
Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press). | ||||||||||
Machine Learning Experiments | 1,552 | 5 months ago | 7 | mit | Jupyter Notebook | |||||
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo | ||||||||||
Bmf | 595 | 4 months ago | 4 | August 22, 2023 | 19 | apache-2.0 | C++ | |||
Cross-platform, customizable multimedia/video processing framework. With strong GPU acceleration, heterogeneous design, multi-language support, easy to use, multi-framework compatible and high performance, the framework is ideal for transcoding, AI inference, algorithm integration, live video streaming, and more. |