27 min listen
LM101-081: Ch3: How to Define Machine Learning (or at Least Try)
LM101-081: Ch3: How to Define Machine Learning (or at Least Try)
ratings:
Length:
37 minutes
Released:
Apr 9, 2020
Format:
Podcast episode
Description
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 3 of my new book which discusses how to formally define machine learning algorithms. Briefly, a learning machine is viewed as a dynamical system that is minimizing an objective function. In addition, the knowledge structure of the learning machine is interpreted as a preference relation graph which is implicitly specified by the objective function. In addition, this week we include in our book review section a new book titled “The Practioner’s Guide to Graph Data” by Denise Gosnell and Matthias Broecheler. To find out more information visit the website: www.learningmachines101.com .
Released:
Apr 9, 2020
Format:
Podcast episode
Titles in the series (85)
LM101-022: How to Learn to Solve Large Constraint Satisfaction Problems: In this episode we discuss how to learn to solve constraint satisfaction inference problems. by Learning Machines 101