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Python Data Science Handbook: full text in Jupyter Notebooks
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 ;)
A game theoretic approach to explain the output of any machine learning model.
The "Python Machine Learning (1st edition)" book code repository and info resource
The "Python Machine Learning (2nd edition)" book code repository and info resource
The "Python Machine Learning (3rd edition)" book code repository
The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"
Lectures on scientific computing with python, as IPython notebooks.
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
Tutorials on how to use pandas effectively to do data analysis
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.
[RETIRED] See Voilà as a supported replacement
An intro to Python & programming for wanna-be data scientists
Scikit-learn tutorial at SciPy2016
Code for a tutorial on Bayesian Statistics by Allen Downey.
Public Repository for cs109a, 2017 edition
Parallel computing in Python tutorial materials
Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller
Code for a workshop on statistical interference using computational methods in Python.
A Python implementation of Seasonal and Trend decomposition using Loess (STL) for time series data.
Introduction to Statistical Modeling with Python (PyCon 2017)
Pandas tutorial for SciPy2015 and SciPy2016 conference
Jupyter notebooks from my O'Reilly Media course "Matplolib for Developers: Data Visualization and Analysis with Python"
Reproducible Data Analysis Workflow in Jupyter
Auto-launching the RISE plugin for Binder presentations.
SymPy tutorial materials for SciPy 2016