LM101-086: Ch8: How to Learn the Probability of Infinitely Many Outcomes
This 86th episode of Learning Machines 101 discusses the problem of asg probabilities to a...
35:28
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...
30:50
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...
33:12
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...
34:21
LM1010-082: 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...
29:04
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...
37:19
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...
31:42
LM101-079: Ch1: How to View Learning as Risk Minimization
This particular podcast covers the material in Chapter 1 of my new (unpublished) book...
26:06
LM101-079: Ch1: How to View Learning as Risk Minimization
This particular podcast covers the material in Chapter 1 of my new (unpublished) book...
26:06
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...
39:17
LM101-077: How to Choose the Best Model using BIC
In this 77th episode of www.learningmachines101.com , we explain the proper semantic...
24:14
LM101-076: How to Choose the Best Model using AIC and GAIC
In this episode, we explain the proper semantic interpretation of the Akaike Information...
28:16
LM101-075: Can computers think? A Mathematician's Response (remix)
In this episode, we explore the question of what can computers do as well as what computers can’t...
36:25
LM101-074: How to Represent Knowledge using Logical Rules (remix)
In this episode we will learn how to use “rules” to represent knowledge. We discuss how this...
19:21
LM101-073: How to Build a Machine that Learns to Play Checkers (remix)
This is a remix of the original second episode Learning Machines 101 which describes in a little...
24:57
LM101-072: Welcome to the Big Artificial Intelligence Magic Show! (Remix of LM101-001 and LM101-002)
This podcast is basically a remix of the first and second episodes of Learning Machines 101 and...
22:06
LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets
In this podcast, we provide some insights into the complexity of common sense. First, we discuss...
31:39
This 70th episode of Learning Machines 101 we discuss how to identify facial emotion expressions...
32:03
LM101-069: What Happened at the 2017 Neural Information Processing Systems Conference?
This 69th episode of Learning Machines 101 provides a short overview of the 2017 Neural...
23:19
This 68th episode of Learning Machines 101 discusses a broad class of unsupervised, supervised,...
21:48
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