This tutorial has its public debut at SciPy 2019. In this tutorial, I showed the class the fundamentals of deep learning in the form of “model, loss, optimizer”.

The GitHub repository can be found here.

I have taught Bayesian statistical modelling with Hugo Bowne-Anderson at SciPy 2018. Our tutorial takes on two parts. Firstly, we build our participants' intuition for Bayes' rule using computational simulation methods. Secondly, we then segue into the abstractions of probabilistic programming to solve problems, including estimation, comparison, and regression.

Notebooks are available here.

I taught myself graph theory in graduate school, as a tool for analyzing influenza evolutionary trajectories. Borrowing the theme of Allen Downey's "X Made Simple" series, I have started my own Network Analysis Made Simple series of Jupyter notebooks, to share this knowledge freely with everybody.

Notebooks are available here.

Based on material from my Network Analysis Made Simple tutorial, I have created two courses on DataCamp titled Network Analysis with Python.

After two PyCons and one SciPy conference, I became convinced of the need to apply software engineering principles to data analytics. One theme that I identified was the need for the practice of (semi-)automated data checks. After meeting with Renee Chu at PyCon 2016, we are collaborating on developing tutorial material to teach how to write data and unit tests.

Notebooks are available here.

As part of my time at Insight, I led mini-workshops on web development and Bokeh, Pythonic code style & code linting, and co-led mini-workshops on deep learning.

Here's a collection of repositories that were involved in teaching this:

I had noticed a growing interest in the use of machine learning (ML) to answer tough biological questions at the Broad Institute. During graduate school, I had taught myself the practical aspects of ML through the `scikit-learn`

API; I found it to be a great introductory path into machine learning. In collaboration with Andres Colubri, David Dao and Jane Hung (Broad Institute), we put together a workshop for members of the Broad Community, with the materials freely available.

Notebooks are available here.