An Attempt at Demystifying Graph Deep Learning

In this talk, inspired by my 2017 attempt at demystifying Bayesian deep learning, I now attempt to demystify graph deep learning.

Computational Biology in Bioengineering

Virtual fireside chat about how computational biology shows up in Bioengineering.

How Software Skillsets Will Accelerate Your Data Science Work

Me explaining exactly what I state in the title!👆

An Attempt at Demystifying Bayesian Deep Learning

In which I tell you why Bayesian deep learning is nothing really special, delivered at PyData NYC 2017.

Bayesian Statistical Analysis with Python

How to do parameter estimation and case/control comparison in PyMC3, delivered at PyCon 2017.

Beyond Two Groups: Generalized A/B[/C/D/E...] Testing

My rant against canned statistical procedures, delivered at PyCon 2019.

Modern, Principled Data Science Workflow

In this talk, I share five key principles, learned from the software development world, that help accelerate data science project development and amplify impact.

Networks, Networks Everywhere!

The many places that graphs can be found, delivered at Big Data Boston 2016 and hosted by DataCamp.

Testing for Data Scientists

How data scientists can incorporate testing into their development, delivered at PyData Ann Arbor in Jan 2020.