Media Summary: We study the main definitions in Generative Learning. We then look into the Naive Bayes algorithm, the most basic generative ... We study the discriminative and generative models. We see that many classical computational models we use in practice are ... We study the problem of density learning which is the cornerstone of probabilistic modeling. We understand the model, data and ...
Genai Ece Uoft Lecture 3 - Detailed Analysis & Overview
We study the main definitions in Generative Learning. We then look into the Naive Bayes algorithm, the most basic generative ... We study the discriminative and generative models. We see that many classical computational models we use in practice are ... We study the problem of density learning which is the cornerstone of probabilistic modeling. We understand the model, data and ... We study LLMs which are Large LMs trained on large corpora. We see how they can be evaluated, fine-tuned, and/or deployed ... We talk about Boltzmann distribution and how we could use it to build a distribution model from an arbitrary computational model. This video is part of Deep Dive 1 of AI Fluency: Framework & Foundations, a course developed by Anthropic, Prof. Rick Dakan ...
Unfortunately, the recording did not work, so this is an older recording from last year.) We start with GANs. We see that though ...
