How deep learning can be used for tabular datasets
Today I’m speaking with Yury Gorishniy about the state of the competition between Deep Learning and Gradient Boosted Decision Trees when it comes to tabular datasets, and about a recent paper he publi...
23 Heinä 20221h 25min
When is missing data not a problem?
Today we’ll be speaking with Julian Morimoto about missing data, its impact on the reliability of statistical inference, and two theorems that he recently discovered using concepts from real analysis ...
23 Heinä 202255min
Why this show
In this episode, Adam introduces the show, the motivations for it, and why and how you should participate.
23 Heinä 20224min
Are your experiments reproducible?
Today we're speaking with Luigi Quaranta about the state of reproducibility in machine learning. Luigi published a taxonomy of support for reproducibility by various tools in the space and together w...
23 Heinä 202252min
Manipulating Your Reputation
In this episode, Adam speaks with Doctor Torsten Ensslin about simulating reputation networks and their manipulation using Information Theory. Torsten is an Astrophysicist and cosmologist at the Max ...
30 Touko 202257min
Multi-Objective AutoML
In this episode, Adam discusses Multi-objective optimization with Laurent Parmentier. Laurent works at OVHCloud, most recently as a data scientist but previously in various software engineering roles....
23 Touko 202248min
ML Interpretability with Jessica Schrouff
This episode launches us into the deep waters of ML interpretability with Jessica Schrouff. Jessica is a Senior Research Scientist at Google Research working on machine learning for healthcare. Before...
16 Touko 20221h 1min
Continual Learning with Iman Mirzadeh
This is a conversation between data scientist Ankush Garg, from Telepath, and fourth-year Ph.D. student Iman Mirzadeh and they’ll be talking about Continual Learning and about Iman’s paper titled “Arc...
2 Touko 202233min
