Stars
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
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 ;)
Python programs, usually short, of considerable difficulty, to perfect particular skills.
Public facing notes page
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Python code for "Probabilistic Machine learning" book by Kevin Murphy
A scikit-learn compatible neural network library that wraps PyTorch
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
Beaker Extensions for Jupyter Notebook
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
Handout for the tutorial "Creating publication-quality figures with matplotlib"
A pedagogical implementation of Autograd
My Machine Learning blog
Lectures for INFO8006 Introduction to Artificial Intelligence, ULiège
Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller
Gaussian Process and Uncertainty Quantification Summer School 2017