- 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.
Google AI Professional Certificate - Learn AI Skills That Get You Hired
Power BI Fundamentals - Create visualizations and dashboards from scratch
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
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
Reviews
4.5 rating, based on 2 Class Central reviews
Showing Class Central Sort
-
The course was excellent, and I was very satisfied with it because it greatly enhanced my knowledge.
-
That was great learning with Class Central. I am very thankful for giving me this opportunity. Thanks to the mentor.