Data Science and Machine Learning (Theory and Projects) A to Z - Dimensionality Reduction: The Curse of Dimensionality

The video discusses probability distributions in machine learning, focusing on Bayes Theorem and its application in classification. It compares generative and discriminative modeling, highlighting the curse of dimensionality and its impact on data requirements. The video concludes with an introduction to dimensionality reduction techniques, specifically PCA.

What is the role of confidence in classification models?

Describe the process of estimating probabilities in a multi-dimensional feature space.

How can dimensionality reduction techniques help in machine learning?

What is principal component analysis (PCA) and how does it relate to dimensionality reduction?