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Stanford Sp21-EE-392B-01 Industrial AI - Shared screen with speaker view
ayush kanodia
28:19
What is the difference between a stats problem and an ML problem?
ayush kanodia
28:51
(Jim talked about people mentioning ML when they were really asking OR or Stats questions; maybe an example will help to think between them)
ayush kanodia
34:02
can I think of a statistical problem is one which leverages more traditional regression style models rather than deep neural networks, but still in both cases you are caring about prediction accuracy but not about what the model parameters and model robustness?
ayush kanodia
34:32
(we can take this later too)
xavier gonzalez
38:20
when you are looking for "qualified hires," what are the qualification you are looking for? what do people tend to lack?
colin@e2eanalytics.com
38:34
Will answer both of these shortly.
ayush kanodia
44:04
Thank you for the answer!
xavier gonzalez
54:19
what are the companies that are mature enough to allow for research papers
xavier gonzalez
01:04:09
what is a SKU?
Fernando Constantino
01:04:25
A specific product
Paritosh Desai
01:07:49
Great example to illustrate the unintended effects and their measruements
daniel oneill
01:07:56
Could you comment on Transfer Learning (say GPT-3) on explainability?