Ensemble learning is all about using multiple models to combine their prediction power to get better predictions that has low variance. Bagging and boosting are two popular techniques that allows us to tackle high variance issue. In this video we will learn about bagging with simple visual demonstration. We will also right python code in sklearn to use BaggingClassifier. And oh yes, in the end we have the exercise for you, as always!
Code: https://github.com/codebasics/py/blob...
Exercise: https://github.com/codebasics/py/blob...
⭐️ Timestamps ⭐️
00:00 Theory
08:01 Coding
22:25 Exercise
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