- 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.
Overview
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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Reviews
4.5 rating, based on 2 Class Central reviews
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The course was excellent, and I was very satisfied with it because it greatly enhanced my knowledge.
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Naimisha ReddyThat was great learning with Class Central. I am very thankful for giving me this opportunity. Thanks to the mentor.
