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.

Recipes for using Python's pandas library

Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

A library for debugging/inspecting machine learning classifiers and explaining their predictions

A Haskell kernel for the Jupyter project.

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

🪼 a python library for doing approximate and phonetic matching of strings.

Handout for the tutorial "Creating publication-quality figures with matplotlib"

IPython and Jupyter in-depth Tutorial, first presented at PyCon 2012

Course materials for my data pipeline video course with O'Reilly

A Series of Notebooks on how to start with Kafka and Python

Notebook and slides for my talk at Pydata NYC 2018

DEPRECATED Mermaid diagrams in the Jupyter Notebook

code and slides for my PyGotham 2016 talk, "Higher-level Natural Language Processing with textacy"

Slides and code for PyCon Canada 2016 talk.

# pydata2019-nyc-visualization

Examples for PyGotham 2016 Talk