Economic Modeling and Prediction, Charitable Giving, and a Follow Up with Peter Backus

Versioning isn't just for source code. Being able to track changes to data is critical for answering questions about data provenance, quality, and reproducibility. Daniel Whitenack joins me this week ...

3 Feb 201740min

Logistic Regression is a popular classification algorithm. In this episode, we discuss how it can be used to determine if an audio clip represents one of two given speakers. It assumes an output varia...

27 Jan 201720min

Prior work has shown that people's response to competition is in part predicted by their gender. Understanding why and when this occurs is important in areas such as labor market outcomes. A well stru...

20 Jan 201734min

Deep learning can be prone to overfit a given problem. This is especially frustrating given how much time and computational resources are often required to converge. One technique for fighting overfit...

13 Jan 201715min

In this episode I speak with Clarence Wardell and Kelly Jin about their mutual service as part of the White House's Police Data Initiative and Data Driven Justice Initiative respectively. The Police D...

6 Jan 201749min

We close out 2016 with a discussion of a basic interview question which might get asked when applying for a data science job. Specifically, how a library might build a model to predict if a book will ...

30 Dec 201635min

Today's episode is a reading of Isaac Asimov's Franchise.  As mentioned on the show, this is just a work of fiction to be enjoyed and not in any way some obfuscated political statement.  Enjoy, and h...

23 Dec 201639min

Classically, entropy is a measure of disorder in a system. From a statistical perspective, it is more useful to say it's a measure of the unpredictability of the system. In this episode we discuss how...

16 Dec 201616min