Model, loss, and optimizer: the core components of deep learning. Come learn more; at the end, we even build the beginnings of a deep learning framework!
Bayesian statistical analysis concepts, taught using PyMC3, with Hugo Bowne-Anderson.
My take on teaching network analysis and graph theory concepts, using NetworkX. Taught at many conferences since 2015.
I created the network analysis curriculum on DataCamp with Hugo Bowne-Anderson.
In this tutorial, we show data scientists how to write tests. Idea hatched with Renee Chu.
One of my earliest tutorials, on how to use
scikit-learn. Delivered in 2015.