Feature Selection and Feature Engineering

The video tutorial covers the concepts of feature selection and feature engineering in machine learning. It explains the difference between features and labels, the importance of selecting relevant features, and the benefits of reducing redundancy. The tutorial also introduces feature engineering as a method to create new features to enhance predictive power. Practical examples and questions are provided to reinforce understanding.

How can minimum redundancy and maximum relevance be achieved in feature selection?

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What are the benefits of selecting relevant features in a machine learning model?

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Describe a scenario where feature engineering could improve the predictive power of a model.

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