Lectures on Topics in Machine Learning

Linear Regression

Notes: Linear Regression html pdf

Videos:

• Simple Linear Regression
• Linear Regression - Geometry
• Multivariate Regression - Introduction
• Multivariate Regression - Calculus
• Multivariate Regression - Geometry
• Multivariate Regression - Centered Coordinates

Lab: Linear Regression lab - includes datafiles and ipynb file. zip tgz

Probability

Notes:

• Probability Notes html pdf
• Naive Bayes Notes html pdf

Videos:

• Probability Basics
• Conditional Probability 1
• Conditional Probability 2
• Probability - Independence
• Probability - Random Variables 1
• Probability - Random Variables 2
• Probability - Expectation and Variance
• Probability - Statistical Models
• Intro to Bayesian Inference
• Bayesian Coin Flipping

Lab: Naive Bayes Lab - includes datafiles and ipynb file. zip tgz

Principal Component Analysis

Notes: Principal Component Analysis html pdf

Videos:

• Variance, Covariance, Correlation, and the Covariance Matrix
• Scores
• Geometry of Scores
• Principal Directions - First Look
• Finding the Principal Directions
• The Spectral Theorem
• Dimension Reduction
• Loadings

Lab: PCA Lab – includes notebook(s) and data zip tgz

Support Vector Machines

Notes: Notes on support vector machines html pdf

Videos:

• Introduction
• Optimal Margins
• Convexity, Convex Hulls, and Supporting Hyperplanes
• Closest Points and Optimal Margins 1
• Closest Points and Optimal Margins 2
• Formulating the Optimization Problem
• The SMO Algorithm
• Kernels, inseparable sets, multiclass classification

Lab: Support Vector Machines Lab (includes jupyter notebook and data files) zip tgz