Introduction to Machine Learning with Matlab

Course Overview

Video: Machine Learning with Matlab

Course Example - Basketball Player Statistics

Getting Starting with Data

Exercise: Importing Data

Exercise: Using Logical Indexing

Exercise: Creating Categorical Data

Exercise: Grouping Data

Exercise: Merging and Visualizing Data

Exercise: Merging and Visualizing Data

Exercise: Normalizing Data

Exercise: Basketball Statistics Script

Finding Natural Patterns in the Data

Clustering Basketball Players

Video: Clustering Basketball Players

Low Dimensional Visualization

To effectively visualize the data containing more than three predictors, you can use the dimensionality reduction techniques such as multidimensional scaling and principal component analysis (PCA).

Exercise: Classical Multidimensional Scaling

Exercise: Nonclassical Multidimensional Scaling

Exercise: Basketball Players

k-Means Clustering

Video: What is k-Means Clustering

Exercise: k-Means Clustering

Exercise: Options for k-Means Clustering

Exercise: Basketball Players

Gaussian Mixture Models

Video: What are Gaussian Mixture Models

Exercise: GMM Clustering

Exercise: Basketball Players

Interpreting the Clusters

Exercise: parallelcoords

Exercise: cross-tabulation

Exercise: Silhouette Plots

Exercise: Basketball Players

Hierarchical Clustering

Video: Hierarchical Clustering

Exercise: Determine Hierarchical Structure

Exercise: Divide Hierarchical Tree into Clusters

Exercise: Basketball Players

Building Classification Models

Course Example: Heart Disease

Video: Heart Disease Classification

Preparing Data

Video: Training and Validation Data

Exercise: Making Training and Test Sets

Exercise: Heart Health

Fitting and Predicting

Exercise: Fitting and Predicting

Exercise: Using a Classification Variable

Evaluating the Classification

Exercise: Prediction and Resubstitution Loss

Exercise: Confusion and Cost Matrix

Exercise: Heart Health

Classification Methods

Course Example: Different Methods to Classify Heart Patients

Video: Classification Learner App

Exercise: Classification Learner App

Nearest Neighbor Classification

Video: What is k-NN?

Exercise: Using Nearest Neighbor Classification with Tables

Exercise: Heart Health

Classification Trees

Video: What is a Classification Tree?

Exercise: Using Classification Trees

Exercise: Heart Health – Numeric Data

Exercise: Heart Health – Numeric and Categorical Data

Naive Bayes Classification

Video: What is Naive Bayes?

Exercise: Using Naive Bayes Classification

Exercise: Heart Health – Numeric Data

Exercise: Heart Health – Numeric and Categorical Data

Discriminant Analysis

Video: What is Discriminant Analysis??

Exercise: Using Discriminant Analysis

Exercise: Heart Health

Support Vector Machines

Video: What are Support Vector Machines?

Exercise: Using Support Vector Machine Classification

Exercise: Concentric Data

Exercise: Heart Health – Numeric Data

Exercise: Heart Health – Numeric and Categorical Data

Multiclass Support Vector Machines

Exercise: Using Multiclass Support Vector Machine Classification

Exercise: Heart Health – Numeric Data

Exercise: Heart Health – Numeric and Categorical Data

Improving Predictive Models

Methods for Improving Predictive Models

Cross Validation

Video: What is Cross Validation?

Exercise: Cross Validation

Exercise: Heart Health

Reducing Predictors - Feature Transformation

Exercise: PCA

Exercise: Heart Health

Reducing Predictors - Feature Selection

Exercise: Built-in Feature Selection

Exercise: Heart Health – Built-in Feature Selection

Exercise: Sequential Feature Selection

Exercise: Heart Health – Sequential Feature Selection

Exercise: Creating Dummy Variables

Exercise: Heart Health – Feature Selection with Categorical Data

Ensemble Learning

Exercise: Creating Ensembles

Exercise: Using Templates

Exercise: Heart Health

Building Regression Models

Course Example - Fuel Economy

Linear Models

Video: What is Linear Regression?

Exercise: Fitting a Line

Exercise: Fitting a Polynomial

Exercise: Multivariable Linear Regression

Exercise: Multivariable Linear Regression with Numeric Arrays

Exercise: Fuel Economy

SVMS and Trees

Exercise: Using Tree and SVM Models

Exercise: Choosing a Regression Model

Exercise: Fuel Economy – Tree

Exercise: Fuel Economy – SVM

Gaussian Process Regression

Video: What is Gaussian Process Regression?

Exercise: Using GPR

Exercise: Using GPR with Outliers

Exercise: Fuel Economy - GPR

Regularized Linear Models

Exercise: Ridge Regression

Exercise: Lasso Regression

Exercise: Fuel Economy – Ridge Regression

Exercise: Fuel Economy – Lasso Regression

Stepwise Fitting

Exercise: Stepwise Feature Selection

Exercise: Fuel Economy

Creating Neural Networks

Overview of Neural Networks

Video: What are Neural Networks?

Self-Organizing Maps

Video: What are Self-Organizing Maps?

Video: Interactively Creating SOMs

Exercise: Interactively Creating SOMs

Exercise: Using Commands to Create SOMs

Feed-Forward Networks

Video: What are Feed-Forward Networks?

Video: Interactively Creating Feed-Forward Networks

Exercise: Interactively Creating Feed-Forward Classification Networks

Additional Resources

Videos: Introduction to Machine Learning

Videos: Applied Machine Learning

Machine Learning Quick Start Guide

Machine Learning Workflow E-Book

Statistics and Machine Learning Toolbox

MathWorks Resources