Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Tensorflow Examples | 43,109 | 5 months ago | 218 | other | Jupyter Notebook | |||||
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) | ||||||||||
Amazon Sagemaker Examples | 9,560 | a month ago | 894 | apache-2.0 | Jupyter Notebook | |||||
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker. | ||||||||||
Mlalgorithms | 9,318 | a year ago | 10 | mit | Python | |||||
Minimal and clean examples of machine learning algorithms implementations | ||||||||||
Ml5 Library | 6,134 | 2 | a year ago | 4 | June 14, 2018 | 267 | other | JavaScript | ||
Friendly machine learning for the web! 🤖 | ||||||||||
Industry Machine Learning | 6,077 | 2 years ago | Jupyter Notebook | |||||||
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai) | ||||||||||
Ignite | 4,409 | 49 | 5 months ago | 1,469 | December 10, 2023 | 153 | bsd-3-clause | Python | ||
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. | ||||||||||
Machinelearningnotebooks | 3,832 | 6 months ago | 386 | mit | Jupyter Notebook | |||||
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft | ||||||||||
Artificial Intelligence Deep Learning Machine Learning Tutorials | 3,436 | a year ago | 152 | other | Python | |||||
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more. | ||||||||||
Lit | 3,272 | 1 | 5 months ago | 11 | November 08, 2023 | 97 | apache-2.0 | TypeScript | ||
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface. | ||||||||||
Shogun | 2,981 | 6 months ago | 1 | April 17, 2020 | 425 | bsd-3-clause | C++ | |||
Shōgun |