Friday, April 12, 2024

Understanding Latent Dirichlet Allocation (LDA) — A Information Scientist’s Information (Half 2) | by Louis Chan | Feb, 2024

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LDA Convergence Defined with a Canine Pedigree Mannequin

“What if my a priori understanding of canine breed group distribution is inaccurate? Is my LDA mannequin doomed?”

My spouse requested.

Welcome again to half 2 of the sequence, the place I share my journey of explaining LDA to my spouse. Within the earlier weblog put up, we mentioned how LDA works and the way it may be understood as a canine pedigree mannequin.

This time round, let’s dive into the iterative becoming technique of LDA!

Half 1 (hyperlink):

  • How does LDA work?
  • The way to clarify LDA to a non-technical particular person?

Half 2 (We’re right here now!):

  • How does LDA enhance iteratively?
  • How does LDA converge?
  • Bonus: Get your LDA cheatsheet right here!

Half 3:

  • When to make use of LDA & when to not?
  • How can we use it in Python?
  • What are the options & variants to LDAs (excluding LLMs)?

Let’s get began.

You probably have not learn half 1 of the sequence, I strongly encourage you to learn it first, as we’ll construct on that understanding.

Fast Recap from Half 1



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