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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 174 - Jeremy Kauffman, CEO of Odysee and LBRY for Decentralized Video
May 31

May 31 Episode 174 - Jeremy Kauffman, CEO of Odysee and LBRY for Decentralized Video

Max Sklar
Guest Interview
Episode 173 - The Fourth Turning Part II - Emerging from the Crisis
May 27

May 27 Episode 173 - The Fourth Turning Part II - Emerging from the Crisis

Max Sklar
Cohost Discussion
Episode 172 - The Fourth Turning Part I - Cycles of History
May 24

May 24 Episode 172 - The Fourth Turning Part I - Cycles of History

Max Sklar
Cohost Discussion
Episode 171 - Ransomware, Security First, and Crypto-corporations
May 17

May 17 Episode 171 - Ransomware, Security First, and Crypto-corporations

Max Sklar
Solo Show
Episode 170 - Bayesian Inference Regulations and Network Algorithms
May 10

May 10 Episode 170 - Bayesian Inference Regulations and Network Algorithms

Max Sklar
Solo Show
Episode 169 - Basecamp’s Boundary on Politics
May 3

May 3 Episode 169 - Basecamp’s Boundary on Politics

Max Sklar
Cohost Discussion

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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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