12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

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

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 ;)

The fastai book, published as Jupyter Notebooks

A High-Quality Real Time Upscaler for Anime Video

A collection of various deep learning architectures, models, and tips

Companion webpage to the book "Mathematics For Machine Learning"

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

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

Book about interpretable machine learning

A better notebook for Scala (and more)

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

Face Depixelizer based on "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models" repository.

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative ski…

Chess reinforcement learning by AlphaGo Zero methods.

Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.

An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.

Spit shine for Jupyter notebooks 🧽✨

Code and files of the deep learning model used to win the Nexar Traffic Light Recognition challenge

Thinking in tensors, writing in PyTorch (a hands-on deep learning intro)

Experiments with StyleCLIP