The Case for Learned Index Structures, Part 1: B-Trees
Jeff Dean and his collaborators at Google are turning the machine learning world upside down (again) with a recent paper about how machine learning models can be used as surprisingly effective substit...
22 Jan 201818min
Challenges with Using Machine Learning to Classify Chest X-Rays
Another installment in our "machine learning might not be a silver bullet for solving medical problems" series. This week, we have a high-profile blog post that has been making the rounds for the last...
15 Jan 201818min
The Fourier Transform
The Fourier transform is one of the handiest tools in signal processing for dealing with periodic time series data. Using a Fourier transform, you can break apart a complex periodic function into a bu...
8 Jan 201815min
Statistics of Beer
What better way to kick off a new year than with an episode on the statistics of brewing beer?
2 Jan 201815min
Re - Release: Random Kanye
We have a throwback episode for you today as we take the week off to enjoy the holidays. This week: what happens when you have a markov chain that generates mashup Kanye West lyrics with Bible verses?...
24 Dec 20179min
Debiasing Word Embeddings
When we covered the Word2Vec algorithm for embedding words, we mentioned parenthetically that the word embeddings it produces can sometimes be a little bit less than ideal--in particular, gender bias ...
18 Dec 201718min
The Kernel Trick and Support Vector Machines
Picking up after last week's episode about maximal margin classifiers, this week we'll go into the kernel trick and how that (combined with maximal margin algorithms) gives us the much-vaunted support...
11 Dec 201717min
Maximal Margin Classifiers
Maximal margin classifiers are a way of thinking about supervised learning entirely in terms of the decision boundary between two classes, and defining that boundary in a way that maximizes the distan...
4 Dec 201714min
