Better know a distribution: the Poisson distribution
This is a re-release of an episode that originally ran on October 21, 2018. The Poisson distribution is a probability distribution function used to for events that happen in time or space. It’s super...
2 Mar 202031min
The Lottery Ticket Hypothesis
Recent research into neural networks reveals that sometimes, not all parts of the neural net are equally responsible for the performance of the network overall. Instead, it seems like (in some neural...
23 Feb 202019min
Interesting technical issues prompted by GDPR and data privacy concerns
Data privacy is a huge issue right now, after years of consumers and users gaining awareness of just how much of their personal data is out there and how companies are using it. Policies like GDPR are...
17 Feb 202020min
Thinking of data science initiatives as innovation initiatives
Put yourself in the shoes of an executive at a big legacy company for a moment, operating in virtually any market vertical: you’re constantly hearing that data science is revolutionizing the world and...
10 Feb 202017min
Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng
As demand for data scientists grows, and it remains as relevant as ever that practicing data scientists have a solid methodological and technical foundation for their work, higher education institutio...
2 Feb 202031min
Running experiments when there are network effects
Traditional A/B tests assume that whether or not one person got a treatment has no effect on the experiment outcome for another person. But that’s not a safe assumption, especially when there are netw...
27 Jan 202024min
Zeroing in on what makes adversarial examples possible
Adversarial examples are really, really weird: pictures of penguins that get classified with high certainty by machine learning algorithms as drumsets, or random noise labeled as pandas, or any one of...
20 Jan 202022min
Unsupervised Dimensionality Reduction: UMAP vs t-SNE
Dimensionality reduction redux: this episode covers UMAP, an unsupervised algorithm designed to make high-dimensional data easier to visualize, cluster, etc. It’s similar to t-SNE but has some advanta...
13 Jan 202029min
