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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 38 - Predictions Panel on Virtual Services, Rise of the Outer Suburbs, and Zombie Coins
Oct 29

Oct 29 Episode 38 - Predictions Panel on Virtual Services, Rise of the Outer Suburbs, and Zombie Coins

Max Sklar
Expert Panel
Episode 37 - Naomi Brockwell on Blockchain Tech and Producing for YouTube and TV
Oct 23

Oct 23 Episode 37 - Naomi Brockwell on Blockchain Tech and Producing for YouTube and TV

Max Sklar
Guest Interview
Episode 36 - The Google Graveyard
Oct 15

Oct 15 Episode 36 - The Google Graveyard

Max Sklar
Cohost Discussion
Episode 35 - Camille Fournier and the Manager's Path
Oct 9

Oct 9 Episode 35 - Camille Fournier and the Manager's Path

Max Sklar
Guest Interview
Episode 34 - Data Engineering with Joe Crobak, Foundations of Smart Software
Oct 2

Oct 2 Episode 34 - Data Engineering with Joe Crobak, Foundations of Smart Software

Max Sklar
Guest Interview
Episode 33 – Ads, Bias, Censorship, Democracy
Sep 25

Sep 25 Episode 33 – Ads, Bias, Censorship, Democracy

Max Sklar
Cohost Discussion
Episode 32 - Woohoo no work!
Sep 18

Sep 18 Episode 32 - Woohoo no work!

Max Sklar
Cohost Discussion
Episode 31 - The Problem of Causality with @ShirinMojarad
Sep 11

Sep 11 Episode 31 - The Problem of Causality with @ShirinMojarad

Max Sklar
Guest Interview
Episode 30 - Entropy is a Decision Tree: Game of Thrones Predictions
Sep 4

Sep 4 Episode 30 - Entropy is a Decision Tree: Game of Thrones Predictions

Max Sklar
Solo Show
Episode 29 - Bitcoin, Blockchain, and Decentralization with @clydevanel of the New York State Assembly
Aug 28

Aug 28 Episode 29 - Bitcoin, Blockchain, and Decentralization with @clydevanel of the New York State Assembly

Max Sklar
Guest Interview
Episode 28 - Alex Jones, Jack Dorsey, and the Censorious Social Media Reporters
Aug 22

Aug 22 Episode 28 - Alex Jones, Jack Dorsey, and the Censorious Social Media Reporters

Max Sklar
Cohost Discussion
Episode 27 - Big Algorithm, Fat Tails, and Converging Priors
Aug 17

Aug 17 Episode 27 - Big Algorithm, Fat Tails, and Converging Priors

Max Sklar
Cohost Discussion
Episode 26 - @chrismessina on Conversational Commerce, Relationship Design, and the Future of Brands
Aug 7

Aug 7 Episode 26 - @chrismessina on Conversational Commerce, Relationship Design, and the Future of Brands

Max Sklar
Guest Interview
Episode 25 - The Great Twitter Purge of 2018
Aug 4

Aug 4 Episode 25 - The Great Twitter Purge of 2018

Max Sklar
Solo Show
Episode 24 - Enjoying the A.I. Summer with @christianDHubbs
Jul 26

Jul 26 Episode 24 - Enjoying the A.I. Summer with @christianDHubbs

Max Sklar
Guest Interview
Episode 23 - NLP in the Lands of Foursquare with @kjc9
Jul 18

Jul 18 Episode 23 - NLP in the Lands of Foursquare with @kjc9

Max Sklar
Guest Interview
Episode 22 - Bayes Rulez, Death to P-Hacking
Jul 11

Jul 11 Episode 22 - Bayes Rulez, Death to P-Hacking

Max Sklar
Cohost Discussion
Episode 21 - Probability, Belief, and The Truth
Jul 9

Jul 9 Episode 21 - Probability, Belief, and The Truth

Max Sklar
Solo Show
Episode 20 - Imperfect Bots, Marketplaces, and the AI Economy
Jun 27

Jun 27 Episode 20 - Imperfect Bots, Marketplaces, and the AI Economy

Max Sklar
Cohost Discussion
Episode 19 - Information Theory with @kronosapiens, Horse Racing, and Fractional Bits
Jun 19

Jun 19 Episode 19 - Information Theory with @kronosapiens, Horse Racing, and Fractional Bits

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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