Linear Digressions

Remember last week, when we were talking about how great the ROC curve is for evaluating models? How things change... This week, we're exploring calibrated risk models, because that's a kind of mode...

6 Feb 201714min

This week: everybody's favorite WWII-era classifier metric! But it's not just for winning wars, it's a fantastic go-to metric for all your classifier quality needs.

30 Jan 201715min

If one machine learning model is good, are two models better? In a lot of cases, the answer is yes. If you build many ok models, and then bring them all together and use them in combination to make ...

23 Jan 201713min

As anyone who's encountered a badly translated text could tell you, not all translations are created equal. Some translations are smooth, fluent and sound like a poet wrote them; some are jerky, non-...

16 Jan 201717min

Take Google-size data, the flexibility of a neural net, and all (well, most) of the languages of the world, and what you end up with is a pile of surprises. This episode is about some interesting fea...

9 Jan 201725min

Recently, Google swapped out the backend for Google Translate, moving from a statistical phrase-based method to a recurrent neural network. This marks a big change in methodology: the tried-and-true ...

2 Jan 201718min

Today we are delighted to bring you an interview with Matt Might, computer scientist and medical researcher extraordinaire and architect of President Obama's Precision Medicine Initiative. As the Oba...

26 Dec 201634min

We have the pleasure of bringing you a very special crossover episode this week: our friends at Partially Derivative (another great podcast about data science, you should check it out) recently interv...

18 Dec 201646min