Linear Digressions
In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications.
- Update frequency
- every 6 days
- Average duration
- 19 minutes
- Episodes
- 291
- Years Active
- 2014 - 2020
So long, and thanks for all the fish
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 (t…
00:35:44 |
Sun 26 Jul 2020
A Reality Check on AI-Driven Medical Assistants
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 compute…
00:14:00 |
Sun 19 Jul 2020
A Data Science Take on Open Policing Data
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 co…
00:23:44 |
Mon 13 Jul 2020
Procella: YouTube's super-system for analytics data storage
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 hav…
00:29:48 |
Mon 06 Jul 2020
The Data Science Open Source Ecosystem
Open source software is ubiquitous throughout data science, and enables the work of nearly every data scientist in some way or another. Open source projects, however, are disproportionately maintaine…
00:23:06 |
Mon 29 Jun 2020
Rock the ROC Curve
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 metri…
00:15:52 |
Sun 21 Jun 2020
Criminology and Data Science
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 …
00:30:57 |
Mon 15 Jun 2020
Racism, the criminal justice system, and data science
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 a…
00:31:36 |
Sun 07 Jun 2020
An interstitial word from Ben
A message from Ben around algorithmic bias, and how our models are sometimes reflections of ourselves.
00:05:59 |
Fri 05 Jun 2020
Convolutional Neural Networks
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…
00:21:55 |
Sun 31 May 2020
Stein's Paradox
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, t…
00:27:02 |
Sun 24 May 2020
Protecting Individual-Level Census Data with Differential Privacy
The power of finely-grained, individual-level data comes with a drawback: it compromises the privacy of potentially anyone and everyone in the dataset. Even for de-identified datasets, there can be w…
00:21:19 |
Mon 18 May 2020
Causal Trees
What do you get when you combine the causal inference needs of econometrics with the data-driven methodology of machine learning? Usually these two don’t go well together (deriving causal conclusions…
00:15:27 |
Mon 11 May 2020
The Grammar Of Graphics
You may not realize it consciously, but beautiful visualizations have rules. The rules are often implict and manifest themselves as expectations about how the data is summarized, presented, and annot…
00:35:38 |
Mon 04 May 2020
Gaussian Processes
It’s pretty common to fit a function to a dataset when you’re a data scientist. But in many cases, it’s not clear what kind of function might be most appropriate—linear? quadratic? sinusoidal? some c…
00:20:55 |
Mon 27 Apr 2020
Keeping ourselves honest when we work with observational healthcare data
The abundance of data in healthcare, and the value we could capture from structuring and analyzing that data, is a huge opportunity. It also presents huge challenges. One of the biggest challenges is…
00:19:08 |
Mon 20 Apr 2020
Changing our formulation of AI to avoid runaway risks: Interview with Prof. Stuart Russell
AI is evolving incredibly quickly, and thinking now about where it might go next (and how we as a species and a society should be prepared) is critical. Professor Stuart Russell, an AI expert at UC B…
00:28:58 |
Mon 13 Apr 2020
Putting machine learning into a database
Most data scientists bounce back and forth regularly between doing analysis in databases using SQL and building and deploying machine learning pipelines in R or python. But if we think ahead a few ye…
00:24:22 |
Mon 06 Apr 2020
The work-from-home episode
Many of us have the privilege of working from home right now, in an effort to keep ourselves and our family safe and slow the transmission of covid-19. But working from home is an adjustment for many…
00:29:06 |
Sun 29 Mar 2020
Understanding Covid-19 transmission: what the data suggests about how the disease spreads
Covid-19 is turning the world upside down right now. One thing that’s extremely important to understand, in order to fight it as effectively as possible, is how the virus spreads and especially how m…
00:25:25 |
Mon 23 Mar 2020
Disclaimer: The podcast and artwork embedded on this page are the property of Ben Jaffe and Katie Malone ([email protected]). This content is not affiliated with or endorsed by eachpod.com.