Today we’re joined by William Fehlman, director of data science at USAA, to discuss:

• His work on topic modeling, which USAA uses in various scenarios, including member chat channels.

• How their datasets are generated.

• Explored methodologies of topic modeling, including latent semantic indexing, latent Dirichlet allocation, and non-negative matrix factorization.

• We also explore how terms are represented via a document-term matrix, and how they are scored based on coherence.

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