Linear Digressions
Total duration:
16 h 41 min
So long, and thanks for all the fish
Linear Digressions
35:44
A Reality Check on AI-Driven Medical Assistants
Linear Digressions
14:00
A Data Science Take on Open Policing Data
Linear Digressions
23:44
Procella: YouTube's super-system for analytics data storage
Linear Digressions
29:48
The Data Science Open Source Ecosystem
Linear Digressions
23:06
Rock the ROC Curve
Linear Digressions
15:52
Criminology and Data Science
Linear Digressions
30:57
Racism, the criminal justice system, and data science
Linear Digressions
31:36
An interstitial word from Ben
Linear Digressions
05:59
Convolutional Neural Networks
Linear Digressions
21:55
Stein's Paradox
Linear Digressions
27:02
Protecting Individual-Level Census Data with Differential Privacy
Linear Digressions
21:19
Causal Trees
Linear Digressions
15:27
The Grammar Of Graphics
Linear Digressions
35:38
Gaussian Processes
Linear Digressions
20:55
Keeping ourselves honest when we work with observational healthcare data
Linear Digressions
19:08
Changing our formulation of AI to avoid runaway risks: Interview with Prof. Stuart Russell
Linear Digressions
28:58
Putting machine learning into a database
Linear Digressions
24:22
The work-from-home episode
Linear Digressions
29:06
Understanding Covid-19 transmission: what the data suggests about how the disease spreads
Linear Digressions
25:25
Network effects re-release: when the power of a public health measure lies in widespread adoption
Linear Digressions
26:40
Causal inference when you can't experiment: difference-in-differences and synthetic controls
Linear Digressions
20:48
Better know a distribution: the Poisson distribution
Linear Digressions
31:51
The Lottery Ticket Hypothesis
Linear Digressions
19:45
Interesting technical issues prompted by GDPR and data privacy concerns
Linear Digressions
20:26
Thinking of data science initiatives as innovation initiatives
Linear Digressions
17:27
Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng
Linear Digressions
31:36
Running experiments when there are network effects
Linear Digressions
24:45
Zeroing in on what makes adversarial examples possible
Linear Digressions
22:51
Unsupervised Dimensionality Reduction: UMAP vs t-SNE
Linear Digressions
29:34
Data scientists: beware of simple metrics
Linear Digressions
24:47
Communicating data science, from academia to industry
Linear Digressions
26:15
Optimizing for the short-term vs. the long-term
Linear Digressions
19:24
Interview with Prof. Andrew Lo, on using data science to inform complex business decisions
Linear Digressions
27:46
Using machine learning to predict drug approvals
Linear Digressions
25:00
Facial recognition, society, and the law
Linear Digressions
43:09
Lessons learned from doing data science, at scale, in industry
Linear Digressions
28:00
Varsity A/B Testing
Linear Digressions
36:00
The Care and Feeding of Data Scientists: Growing Careers
Linear Digressions
25:19
The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists
Linear Digressions
20:16