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Machine Learning Onramp

MathWorks via MATLAB Academy

Overview

  • Overview of Machine Learning: Familiarize yourself with machine learning concepts and the course.
  • Classification Workflow: Build a simple model to perform a classification task.
  • Importing and Preprocessing Data: Import data from multiple files.
  • Engineering Features: Calculate features from raw signals.
  • Classification Models: Train and use Machine Learning models to make predictions.
  • Conclusion: Learn next steps and give feedback on the course.

Syllabus

  • What is Machine Learning
  • Overview
  • Import Data
  • Process Data
  • Extract Features
  • Build a Model
  • Evaluate the Model
  • Review
  • Organization of Data Files
  • Creating Datastores
  • Adding a Data Transformation
  • Types of Signals
  • Calculating Summary Statistics
  • Finding Peaks
  • Computing Derivatives
  • Calculating Correlations
  • Automating Feature Extraction
  • Training and Testing Data
  • Machine Learning Models
  • Training a Model
  • Making Predictions
  • Investigating Misclassifications
  • Improving the Model
  • Additional Resources
  • Survey

Taught by

Matt Tearle

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