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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