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I am looking for a recommendation for basic introductory material on Bayesian Non-parametric methods, specifically Dirichlet Process / Chinese Restaurant Process. I am looking for material which covers the modeling part as well as the inference part from ground-up.

Most of the material I found on the internet has slightly advanced material and they skip the inference part, which is usually harder to grasp.

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I would recommend Tamara Broderick's 3-part tutorial series from MLSS. She explains both modeling + inference using these methods from the ground up and focuses on the intuition.

Links to part 1, part 2, and part 3.

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