Google Research

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 ;)

The fastai deep learning library

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

A game theoretic approach to explain the output of any machine learning model.

Python programs, usually short, of considerable difficulty, to perfect particular skills.

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

this repository accompanies the book "Grokking Deep Learning"

A course in reinforcement learning in the wild

An adversarial example library for constructing attacks, building defenses, and benchmarking both

A scikit-learn compatible neural network library that wraps PyTorch

Reference models and tools for Cloud TPUs.

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

FMA: A Dataset For Music Analysis

Machine learning lessons and teaching projects designed for engineers

Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

A curated list of awesome embedding models tutorials, projects and communities.

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Tutorials and training material for the H2O Machine Learning Platform

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

A list of NLP(Natural Language Processing) tutorials

ktrain is a Python library that makes deep learning and AI more accessible and easier to apply

Distributed deep learning on Hadoop and Spark clusters.

Lab materials for the Full Stack Deep Learning Course