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What is Machine Learning in Signal Processing about?

This document summarizes machine learning techniques for signal processing taught in a course. It discusses linear discriminant analysis, which finds a linear transformation to maximize class separation by maximizing between-class distance and minimizing within-class covariance. It also compares principal component analysis and linear discriminant analysis, and discusses different representations of data like text and audio, specifically bag-of-words models, TF-IDF for text, and spectrograms for audio repre

Author

lubhawan parihar

Language

EN