In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications.
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Network effects re-release: when the power of a public health measure lies in widespread adoption
This week’s episode is a re-release of a recent e…
Causal inference when you can't experiment: difference-in-differences and synthetic controls
When you need to untangle cause and effect, but y…
Better know a distribution: the Poisson distribution
This is a re-release of an episode that originall…
Interesting technical issues prompted by GDPR and data privacy concerns
Data privacy is a huge issue right now, after yea…
Thinking of data science initiatives as innovation initiatives
Put yourself in the shoes of an executive at a bi…
Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng
As demand for data scientists grows, and it remai…
Running experiments when there are network effects
Traditional A/B tests assume that whether or not …
Zeroing in on what makes adversarial examples possible
Adversarial examples are really, really weird: pi…
Unsupervised Dimensionality Reduction: UMAP vs t-SNE
Dimensionality reduction redux: this episode cove…