31 min listen
LM101-029: How to Modernize Deep Learning with Rectilinear units, Convolutional Nets, and Max-Pooling
LM101-029: How to Modernize Deep Learning with Rectilinear units, Convolutional Nets, and Max-Pooling
ratings:
Length:
36 minutes
Released:
May 25, 2015
Format:
Podcast episode
Description
This podcast discusses talks, papers, and ideas presented at the recent International Conference on Learning Representations 2015 which was followed by the Artificial Intelligence in Statistics 2015 Conference in San Diego. Specifically, commonly used techniques shared by many successful deep learning algorithms such as: rectilinear units, convolutional filters, and max-pooling are discussed. For more details please visit our website at: www.learningmachines101.com!
Released:
May 25, 2015
Format:
Podcast episode
Titles in the series (85)
LM101-006: How to Interpret Turing Test Results: Episode Summary: In this episode, we briefly review the concept of the Turing Test for Artificial Intelligence (AI) which states that if a computer.s behavior is indistinguishable from that of the behavior of a thinking human being, by Learning Machines 101