So long, and thanks for all the fish
Linear Digressions
by Ben Jaffe and Katie Malone
3y ago
All good things must come to an end, including this podcast. This is the last episode we plan to release, and it doesn’t cover data science—it’s mostly reminiscing, thanking our wonderful audience (that’s you!), and marveling at how this thing that started out as a side project grew into a huge part of our lives for over 5 years. It’s been a ride, and a real pleasure and privilege to talk to you each week. Thanks, best wishes, and good night! —Katie and Ben ..read more
Visit website
A Reality Check on AI-Driven Medical Assistants
Linear Digressions
by Ben Jaffe and Katie Malone
3y ago
The data science and artificial intelligence community has made amazing strides in the past few years to algorithmically automate portions of the healthcare process. This episode looks at two computer vision algorithms, one that diagnoses diabetic retinopathy and another that classifies liver cancer, and asks the question—are patients now getting better care, and achieving better outcomes, with these algorithms in the mix? The answer isn’t no, exactly, but it’s not a resounding yes, because these algorithms interact with a very complex system (the healthcare system) and other shortcomings of t ..read more
Visit website
A Data Science Take on Open Policing Data
Linear Digressions
by Ben Jaffe and Katie Malone
3y ago
A few weeks ago, we put out a call for data scientists interested in issues of race and racism, or people studying how those topics can be studied with data science methods, should get in touch to come talk to our audience about their work. This week we’re excited to bring on Todd Hendricks, Bay Area data scientist and a volunteer who reached out to tell us about his studies with the Stanford Open Policing dataset ..read more
Visit website
Procella: YouTube's super-system for analytics data storage
Linear Digressions
by Ben Jaffe and Katie Malone
3y ago
This is a re-release of an episode that originally ran in October 2019. If you’re trying to manage a project that serves up analytics data for a few very distinct uses, you’d be wise to consider having custom solutions for each use case that are optimized for the needs and constraints of that use cases. You also wouldn’t be YouTube, which found themselves with this problem (gigantic data needs and several very different use cases of what they needed to do with that data) and went a different way: they built one analytics data system to serve them all. Procella, the system they built, is the to ..read more
Visit website
Rock the ROC Curve
Linear Digressions
by Ben Jaffe and Katie Malone
3y ago
This is a re-release of an episode that first ran on January 29, 2017. 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 ..read more
Visit website
Criminology and Data Science
Linear Digressions
by Ben Jaffe and Katie Malone
4y ago
This episode features Zach Drake, a working data scientist and PhD candidate in the Criminology, Law and Society program at George Mason University. Zach specializes in bringing data science methods to studies of criminal behavior, and got in touch after our last episode (about racially complicated recidivism algorithms). Our conversation covers a wide range of topics—common misconceptions around race and crime statistics, how methodologically-driven criminology scholars think about building crime prediction models, and how to think about policy changes when we don’t have a complete understand ..read more
Visit website
Racism, the criminal justice system, and data science
Linear Digressions
by Ben Jaffe and Katie Malone
4y ago
As protests sweep across the United States in the wake of the killing of George Floyd by a Minneapolis police officer, we take a moment to dig into one of the ways that data science perpetuates and amplifies racism in the American criminal justice system. COMPAS is an algorithm that claims to give a prediction about the likelihood of an offender to re-offend if released, based on the attributes of the individual, and guess what: it shows disparities in the predictions for black and white offenders that would nudge judges toward giving harsher sentences to black individuals. We dig into this al ..read more
Visit website
An interstitial word from Ben
Linear Digressions
by Ben Jaffe and Katie Malone
4y ago
A message from Ben around algorithmic bias, and how our models are sometimes reflections of ourselves ..read more
Visit website
Convolutional Neural Networks
Linear Digressions
by Ben Jaffe and Katie Malone
4y ago
This is a re-release of an episode that originally aired on April 1, 2018 If you've done image recognition or computer vision tasks with a neural network, you've probably used a convolutional neural net. This episode is all about the architecture and implementation details of convolutional networks, and the tricks that make them so good at image tasks ..read more
Visit website
Stein's Paradox
Linear Digressions
by Ben Jaffe and Katie Malone
4y ago
This is a re-release of an episode that was originally released on February 26, 2017. When you're estimating something about some object that's a member of a larger group of similar objects (say, the batting average of a baseball player, who belongs to a baseball team), how should you estimate it: use measurements of the individual, or get some extra information from the group? The James-Stein estimator tells you how to combine individual and group information make predictions that, taken over the whole group, are more accurate than if you treated each individual, well, individually ..read more
Visit website

Follow Linear Digressions on FeedSpot

Continue with Google
Continue with Apple
OR