Inference algorithms and sampling techniques

on YouTube ↗26m

" summary

Covers Monte Carlo-based inference methods for generative probabilistic models, focusing on sampling algorithms such as Gibbs sampling and priors like Dirichlet and Wishart. Walks through applying these techniques to real-world problems, showing step-by-step modeling, algorithm application, and practical challenges encountered when building data science solutions.

AI-written summary · about

" chapters (11)

1. 0:00Start
2. 6:39Joint distributions
3. 10:273D normal distribution around centroid
4. 10:39Probability Distributions
5. 12:22Dirichlet Distribution
6. 13:03Generative model
7. 14:53Inferencing problem
8. 15:57Inferring the parameters
9. 17:37Gibbs sampling (contd)
10. 20:12Code pointers
11. 21:00Resume Parsing - Problem statement

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