Learning Machines 101 Podcast
1) LM101-086: Ch8: How to Learn the Probability of Infinitely Many Outcomes
This 86th episode of Learning Machines 101 discusses the problem of assigning probabilities to a possibly infinite set of outcomes in a space-time continuum which characterizes our physical world. Suc...Show More
2) LM101-085:Ch7:How to Guarantee your Batch Learning Algorithm Converges
This 85th episode of Learning Machines 101 discusses formal convergence guarantees for a broad class of machine learning algorithms designed to minimize smooth non-convex objective functions using bat...Show More
3) LM101-084: Ch6: How to Analyze the Behavior of Smart Dynamical Systems
In this episode of Learning Machines 101, we review Chapter 6 of my book “Statistical Machine Learning” which introduces methods for analyzing the behavior of machine inference algorithms and machine ...Show More
4) LM101-083: Ch5: How to Use Calculus to Design Learning Machines
This particular podcast covers the material from Chapter 5 of my new book “Statistical Machine Learning: A unified framework” which is now available! The book chapter shows how matrix calculus is very...Show More
5) LM101-082: Ch4: How to Analyze and Design Linear Machines
The main focus of this particular episode covers the material in Chapter 4 of my new forthcoming book titled “Statistical Machine Learning: A unified framework.”  Chapter 4 is titled “Linear Algebra f...Show More
6) LM101-081: Ch3: How to Define Machine Learning (or at Least Try)
This particular podcast covers the material in Chapter 3 of my new book “Statistical Machine Learning: A unified framework” with expected publication date May 2020. In this episode we discuss Chapter ...Show More
7) LM101-080: Ch2: How to Represent Knowledge using Set Theory
This particular podcast covers the material in Chapter 2 of my new book “Statistical Machine Learning: A unified framework” with expected publication date May 2020. In this episode we discuss Chapter ...Show More
8) LM101-079: Ch1: How to View Learning as Risk Minimization
This particular podcast covers the material in Chapter 1 of my new (unpublished) book “Statistical Machine Learning: A unified framework”. In this episode we discuss Chapter 1 of my new book, which sh...Show More
9) LM101-078: Ch0: How to Become a Machine Learning Expert
This particular podcast (Episode 78 of Learning Machines 101) is the initial episode in a new special series of episodes designed to provide commentary on a new book that I am in the process of writin...Show More
10) LM101-077: How to Choose the Best Model using BIC
In this 77th episode of www.learningmachines101.com , we explain the proper semantic interpretation of the Bayesian Information Criterion (BIC) and emphasize how this semantic interpretation is fundam...Show More