Machine Learning Onramp

Learn the basics of practical machine learning for classification problems in MATLABĀ®. Use a machine learning model that extracts information from real-world data to group your data into predefined categories.

Course modules

Overview of Machine Learning

Familiarize yourself with machine learning concepts and the course.

Lessons:
  • What is Machine Learning

Classification Workflow

Build a simple model to perform a classification task.

Lessons:
  • Overview
  • Import Data
  • Preprocess Data
  • Extract Features
  • Build a Model
  • Evaluate the Model
  • Review

Import and Preprocess Data

Import data from multiple files.

Lessons:
  • Organization of Data Files
  • Create a Datastore
  • Add a Preprocessing Function

Engineering Features

Calculate features from raw signals.

Lessons:
  • Types of Signals
  • Calculate Summary Statistics
  • Find Peaks in Signals
  • Compute Derivatives
  • Calculate Correlations
  • Automate Feature Extraction

Classification Models

Train and use Machine Learning models to make predictions.

Lessons:
  • Training and Testing Data
  • Machine Learning Models
  • Training a Model
  • Make Predictions
  • Investigate Misclassifications
  • Improve the Model

Conclusion

Learn next steps and give feedback on the course.

Lessons:
  • Additional Resources
  • Survey

Machine Learning with MATLAB

Explore data and build predictive models.

Deep Learning Onramp

Get started quickly using deep learning methods to perform image recognition.

MATLAB for Data Processing and Visualization

Create custom visualizations and automate your data analysis tasks.

MATLAB Onramp

Get started quickly with the basics of MATLAB.