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.
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.
