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Learn how to design, develop, deploy and iterate on production-grade ML applications.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
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 ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
A game theoretic approach to explain the output of any machine learning model.
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.
Companion webpage to the book "Mathematics For Machine Learning"
This repository contains implementations and illustrative code to accompany DeepMind publications
PRML algorithms implemented in Python
Free MLOps course from DataTalks.Club
An open-source, low-code machine learning library in Python
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Flax is a neural network library for JAX that is designed for flexibility.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
Repo for the Deep Learning Nanodegree Foundations program.
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
Code repository for O'Reilly book
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Notebooks about Bayesian methods for machine learning
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
Lectures for INFO8010 Deep Learning, ULiège
Machine learning in Python with scikit-learn MOOC
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected