Learn how to design, develop, deploy and iterate on production-grade ML applications.

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

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

The fastai book, published as Jupyter Notebooks

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

The "Python Machine Learning (1st edition)" book code repository and info resource

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

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

Learn ML engineering for free in 4 months!

An open-source, low-code machine learning library in Python

this repository accompanies the book "Grokking Deep Learning"

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

A scikit-learn compatible neural network library that wraps PyTorch

An annotated implementation of the Transformer paper.

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models l…

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.

Repo for the Deep Reinforcement Learning Nanodegree program

Learn how to design, develop, deploy and iterate on production-grade ML applications.

A crash course in six episodes for software developers who want to become machine learning practitioners.

This is Andrew NG Coursera Handwritten Notes.

A repo for data science related questions and answers

Source code accompanying O'Reilly book: Machine Learning Design Patterns

🤖⚡ 50 scikit-learn tips

A few exercises for use at events.

Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017