Challenge

Project 5

Advantages of Gradient Boosting

provides predictive accuracy, flexibility, No data pre-processing required, Handles missing data

Disadvantages of Gradient Boosting

overfitting, expensive

Your portfolio, next

Ship work like this
in your own course.

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Free 20-minute call. We'll map the right course to where you want to work.

By submitting you agree to our Terms and Privacy Policy.