| 2022 December 9 |
PyData Global 2022 talk on reliable data science |
| 2022 November 3 |
Bayesian equivalent of power analysis |
| 2022 September 30 |
Targeting lead service line projects to minimize childhood exposure |
| 2021 March 7 |
Assigning students to rank-ordered group projects with linear optimization |
| 2020 April 19 |
Dirichlet-multinomial model for Skittle proportions |
| 2016 July 20 |
SciPy 2016: "Data Science is Software" tutorial |
| 2016 July 4 |
From German Tanks to stochastic fortune cookies |
| 2015 December 19 |
Solving the Bayesian German Tank problem with PyMC and PyStan |
| 2015 August 8 |
Speeding up non-vectorizable code with Cython |
| 2015 May 11 |
Code in "Blackhat" is hilariously wrong but recognizable Python |
| 2015 February 26 |
Combinatorial optimization, deterministic and stochastic approaches |
| 2014 December 25 |
Looking at (small) data from five years of driving |
| 2014 October 24 |
My talk on scikit-learn at Statistical Programming DC |
| 2014 September 20 |
Using Pelican to blog with IJulia notebooks (or other languages) |
| 2014 August 27 |
Frogs, flies, and Julia |
| 2014 June 20 |
Using Python for linear optimization |
| 2014 June 16 |
To catch a spy (using Markov chains) |
| 2014 January 8 |
Analyzing Dunkin' Donuts' business with scraped data |
| 2014 January 3 |
Modeling chutes and ladders as a Markov chain |
| 2014 January 1 |
In-mapper combiner pattern for MapReduce |
| 2013 December 30 |
Metropolis-Hastings and slice sampling in Python |
