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This serves as a quick cheat-sheet for solving small Bayesian problems using a table.

Based in Sydney, Australia, Foundry is a blog by Rebecca Thao. Her posts explore modern architecture through photos and quotes by influential architects, engineers, and artists.
The Local Maximum Expand Your Perspective
Episode 275 - Connecticut Chronicles, Columbia Conferences & Questioning Bots
Apr 24

Apr 24 Episode 275 - Connecticut Chronicles, Columbia Conferences & Questioning Bots

Max Sklar
Cohost Discussion
Episode 274 - Quantum Computing with Ian MacCormack
Apr 17

Apr 17 Episode 274 - Quantum Computing with Ian MacCormack

Max Sklar
Guest Interview
Episode 273 - Stop Making AI Boring
Apr 11

Apr 11 Episode 273 - Stop Making AI Boring

Max Sklar
Solo Show
Episode 272 - Data Science History with Chris Wiggins and Matthew Jones
Apr 3

Apr 3 Episode 272 - Data Science History with Chris Wiggins and Matthew Jones

Max Sklar
Guest Interview

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Subscribe on iTunes | Soundcloud | Stitcher | Odysee | Locals

Get Max's Free Cheat-Sheet on Bayesian Inference

Just sign up for the email list to keep up with exciting developments, floating ideas, and new projects from Max and his guests.

Thank you for joining The Local Maximum email list!

Download your free Bayesian Inference Page

This serves as a quick cheat-sheet for solving small Bayesian problems using a table.

The “Local Maximum” is a mathematical term referring to a point at which one needs to step down in order to reach new heights. But people - not just points - can get caught in a local maximum. That's what happens when we've gone as far as we can through one strategy which has gone stale and need to search for new ideas. This podcast is about examining technology, engineering, and social trends by expanding perspectives and moving beyond the Local Maximum both for ourselves and our algorithms.

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