Popular GitHub Repositories for Jupyter Themes

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

? Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

A neural network that transforms a design mock-up into a static website.

Machine Learning Toolkit for Kubernetes

A one stop repository for generative AI research updates, interview resources, notebooks and much more!

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Best Practices, code samples, and documentation for Computer Vision.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Evidently is ??an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Setup and customize deep learning environment in seconds.

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

AI实战-practicalAI 中文版

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可