Data Science and Machine Learning (Theory and Projects) A to Z - Multiple Random Variables: Classification

The video tutorial discusses the construction of probability models for classification, focusing on discrete random variables. It explains the difference between generative and discriminative models, highlighting the challenges in modeling with multiple random variables. The tutorial emphasizes that most modern machine learning models are discriminative, directly modeling the probability distribution without delving into individual components. The video concludes with a preview of the next topic, the naive Bayes classifier.

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