Machine Learning Onramp
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
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
Select a Lesson to Get Started
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
- Components Needed for Transfer Learning
- 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
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