Learning Machines 101

LM101-056: How to Build Generative Latent Probabilistic Topic Models for Search Engine and Recommender System Applications

Informações:

Sinopse

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