Season 1 · Episode 56
LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications
Learning Machines 101 · Richard M. Golden
September 20, 201627m 59s
Audio is streamed directly from the publisher (traffic.libsyn.com) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
In this NEW episode we discuss Latent Semantic Indexing type machine learning algorithms which have a PROBABILISTIC interpretation. We explain why such a probabilistic interpretation is important and discuss how such algorithms can be used in the design of document retrieval systems, search engines, and recommender systems. Check us out at: www.learningmachines101.com
and follow us on twitter at: @lm101talk