MATLAB and Simulink Training

Machine Learning Onramp

Machine Learning

This free, two-hour tutorial provides an interactive introduction to practical machine learning methods for classification problems.

Prerequisites: MATLAB Onramp or basic knowledge of MATLAB

Details and launch

 

Access to MATLAB through your web browser

 

Engaging video tutorials

 

Hands-on exercises with automated assessments and feedback

 

Lessons available in English, Korean, Japanese, and Spanish

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1.

Overview of Machine Learning

Familiarize yourself with machine learning concepts and the course.

  • What is machine learning?
  • Course overview

2.

Classification Workflow

Build a simple model to perform a classification task.

  • Overview of the classification workflow
  • Importing data
  • Processing data
  • Extracting features
  • Building a model
  • Evaluating the model
  • Review

3.

Importing and Preprocessing Data

Import data from multiple files.

  • Organization of data files
  • Creating datastores
  • Adding a data transformation

4.

Engineering Features

Calculate features from raw signals.

  • Types of signals
  • Calculating summary statistics
  • Finding peaks
  • Computing derivatives
  • Calculating correlations
  • Automating feature extraction   

5.

Classification Models

Train and use machine learning models to make predictions.

  • Training and testing
  • Machine learning models
  • Training a model
  • Making predictions
  • Investigating misclassifications
  • Improving the model
Details and launch

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