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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 120 - The Reopening: Confounders, Colliders, and Simpson’s Paradox
May 25

May 25 Episode 120 - The Reopening: Confounders, Colliders, and Simpson’s Paradox

Max Sklar
Solo Show
Episode 119 - Advocating for Bayesian Inference with Brian Blais
May 18

May 18 Episode 119 - Advocating for Bayesian Inference with Brian Blais

Max Sklar
Guest Interview
Episode 118 - Learning vs Memorization, Bitcoin Halvening, and Antibody Tests
May 11

May 11 Episode 118 - Learning vs Memorization, Bitcoin Halvening, and Antibody Tests

Max Sklar
Cohost Discussion
Episode 117 - A.I. Hype and the Expert Problem with Christian Hubbs
May 4

May 4 Episode 117 - A.I. Hype and the Expert Problem with Christian Hubbs

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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