Classification Methods with Machine Learning

Course modules

Introduction

Get an overview of the course.

Lessons:

Course Overview

Course Example

k-Nearest Neighbor Classification

Train k-nearest neighbor models and change hyperparameters such as the number of neighbors and the distance metric.

Lessons:

Overview of k-Nearest Neighbor Classification

Perform k-Nearest Neighbor Classification

Quick Reference

Classification Trees

Train decision tree models for classification and modify the tree branching specifications.

Lessons:

Overview of Classification Trees

Perform Classification with Decision Trees

Quick Reference

Naive Bayes Classification

Train naive Bayes classification models with and without kernels.

Lessons:

Overview of Naive Bayes Classification

Perform Naive Bayes Classification

Quick Reference

Discriminant Analysis Classification

Train linear and quadratic discriminant analysis classification models.

Lessons:

Overview of Discriminant Analysis Classification

Perform Discriminant Analysis Classification

Quick Reference

Support Vector Machine Classification

Train binary and multiclass support vector machine (SVM) classification models and change the kernel hyperparameter.

Lessons:

Overview of Support Vector Machines

Perform Support Vector Machine Classification

Quick Reference

Classification Ensembles

Combine multiple classification models into an ensemble by using techniques such as bagging, boosting, and random subspace.

Lessons:

Overview of Ensemble Learning

Perform Classification with Ensemble Models

Quick Reference

Classification with Neural Networks

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

Lessons:

Overview of Neural Networks

Perform Classification with Neural Networks

Quick Reference

Conclusion

Learn next steps and give feedback on the course.

Lessons:

Additional Resources

Survey

Course modules

Introduction

k-Nearest Neighbor Classification

Classification Trees

Naive Bayes Classification

Discriminant Analysis Classification

Support Vector Machine Classification

Classification Ensembles

Classification with Neural Networks

Conclusion

Language

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

Machine Learning Onramp

Classification Methods with Machine Learning

Course modules

Introduction

k-Nearest Neighbor Classification

Classification Trees

Naive Bayes Classification

Discriminant Analysis Classification

Support Vector Machine Classification

Classification Ensembles

Classification with Neural Networks

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