Regression Methods with Machine Learning

Course modules

Introduction

Get an overview of the course.

Lessons:

Course Overview

Course Example

Linear Regression Models

Train linear regression models using linear, quadratic, and interaction terms.

Lessons:

Overview of Linear Regression Models

Use Linear Regression Models

Quick Reference

Stepwise Linear Regression

Train a stepwise linear regression model by specifying the initial terms and setting an upper bound on the terms.

Lessons:

Overview of Stepwise Linear Regression

Use Stepwise Linear Regression

Quick Reference

Regularized Linear Regression

Train regularized linear regression models by applying a penalty to the coefficient values.

Lessons:

Overview of Regularized Linear Regression

Use Regularized Linear Models

Quick Reference

Support Vector Machine

Train SVM models for regression and change the kernel function hyperparameter.

Lessons:

Overview of Support Vector Machine

Use SVM Models

Quick Reference

Decision Trees and Tree Ensembles

Train decision tree models for regression and change the minimum leaf size hyperparameter. Train ensembles of trees using techniques like bagging and boosting.

Lessons:

Overview of Decision Trees and Tree Ensembles

Use Decision Trees and Tree Ensembles

Quick Reference

Neural Networks

Train neural networks for regression and change hyperparameters such as the number fully connected layers and the layer size.

Lessons:

Overview of Neural Networks

Use Neural Networks

Quick Reference

Gaussian Process Regression

Train GPR models by setting the basis and the kernel functions.

Lessons:

Overview of Gaussian Process Regression

Use Gaussian Process Regression

Quick Reference

Conclusion

Learn next steps and give feedback on the course.

Lessons:

Additional Resources

Survey

Course modules

Introduction

Linear Regression Models

Stepwise Linear Regression

Regularized Linear Regression

Support Vector Machine

Decision Trees and Tree Ensembles

Neural Networks

Gaussian Process Regression

Conclusion

Language

Hands-on exercises with automated feedback
Access to MATLAB through your web browser
Shareable progress report and course certificate

Machine Learning Onramp

Regression Methods with Machine Learning

Course modules

Introduction

Linear Regression Models

Stepwise Linear Regression

Regularized Linear Regression

Support Vector Machine

Decision Trees and Tree Ensembles

Neural Networks

Gaussian Process Regression

Conclusion

Language

Hands-on exercises with automated feedbackAccess to MATLAB through your web browserShareable progress report and course certificate

Machine Learning Onramp

Hands-on exercises with automated feedback
Access to MATLAB through your web browser
Shareable progress report and course certificate