TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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 deep learning library

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

Kubernetes community content

Public facing notes page

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

From the basics to slightly more interesting applications of Tensorflow

fast.ai Courses

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

A python tutorial on bayesian modeling techniques (PyMC3)

An interactive data visualization tool which brings matplotlib graphics to the browser using D3.

General Assembly's 2015 Data Science course in Washington, DC

The hands-on NLTK tutorial for NLP in Python

Speech Recognition with the Caffe deep learning framework, migrating to

An on-premises, bare-metal solution for deploying GPU-powered applications in containers

NBA shot charts using matplotlib, seaborn, and bokeh.