Feature Engineering | Applied Machine Learning, Part 1

Explore how to perform feature engineering, a technique for transforming raw data into features that are suitable for a machine learning algorithm.

Feature engineering starts with your best guess about what features might influence the action you’re trying to predict. After that, it’s an iterative process where you create new features, add them to your model, and see if your results have improved.  

This video provides a high-level overview of the topic, and it uses several examples to illustrate basic principles behind feature engineering and established ways for extracting features from signals, text, and images.

Get started with MATLAB for Machine Learning with these interactive examples. You can run the examples right in your browser to see MATLAB in action: bit.ly/4dIW8w0

Learn more about MATLAB for machine learning: bit.ly/2tUPS0O

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