Principal Component Analysis and Low-Rank Models

The videos below cover the material on Principal Component Analysis and Low-Rank Models from Chapter 1 of the book. See here for the full YouTube playlist. Click on the titles to download the slides.

Overview

Covariance matrix

Principal component analysis

Spectral theorem

Dimensionality reduction

Low-rank models

Matrix completion

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    • Probability
    • Discrete Variables
    • Continuous Variables
    • Multiple Discrete Variables
    • Multiple Continuous Variables
    • Discrete and Continuous
    • Averaging
    • Correlation
    • Estimation of Population Parameters
    • Hypothesis Testing
    • PCA and Low-Rank Models
    • Regression and Classification
    • Causal Inference
  • Code
    • Probability
    • Discrete Variables
    • Continuous Variables
    • Multiple Discrete Variables
    • Multiple Continuous Variables
    • Discrete and Continuous
    • Averaging
    • Correlation
    • Estimation of Population Parameters
    • Hypothesis Testing
    • PCA and Low-Rank Models
    • Regression and Classification
  • Solutions

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