Machine Learning with MATLAB

Learn to create regression, classification, and clustering models and improve their performance.

Prerequisites: MATLAB Fundamentals

This course is included with select licenses. Click here to purchase.

Benefits of the Self-Paced Format

Step-by-step instruction

Hands-on exercises with automated feedback

Access to MATLAB through your web browser

Shareable progress report and course certificate

About This Course

 Lessons are available only in English.


1.

Getting Started

Get an overview of the course. Import and process data, explore data features, and train and evaluate a classification model.

30 mins


2.

Finding Natural Patterns in Data

Use unsupervised learning techniques to group observations based on a set of explanatory variables and discover natural patterns in a data set.

120 mins


3.

Classification Methods

Use available classification methods to train data classification models. Make predictions and evaluate the accuracy of a predictive model.

135 mins


4.

Improving Predictive Models

Validate model performance. Optimize model properties. Reduce the dimensionality of a data set and simplify machine learning models.

90 mins


5.

Regression Methods

Use supervised learning techniques to perform predictive modeling for continuous response variables.

105 mins


6.

Neural Networks

Create and train neural networks for clustering and predictive modeling. Adjust network architecture to improve performance.

45 mins

Related Courses

MATLAB Fundamentals

Learn core MATLAB functionality for data analysis, modeling, and programming.

Machine Learning Onramp

Learn the basics of practical machine learning methods for classification problems.

Deep Learning with MATLAB

Learn the theory and practice of building deep neural networks with real-life image and sequence data.

Looking for a Classroom Option?

Machine Learning with MATLAB is also offered in an instructor-led format.