LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications - a podcast by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

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

 

Further episodes of Learning Machines 101

Further podcasts by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

Website of Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.