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Boosting

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Overview

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This course explains boosting within ensemble learning, covering bias and variance, ensemble methods, exploratory data analysis, decision-tree model building, AdaBoost, Gradient Boosting, XGBoost, and bagging versus boosting.

Syllabus

Introduction.
Did you know?.
Introduction to Bias and Variance.
Ensemble Methods.
Boosting.
Understanding Datasets.
EDA.
Model Building for Decision Tree Model.
How Boosting Algorithm works?.
AdaBoost Classifier.
Gradient Boosting Classifier.
XGBoost Classifier.
Bagging vs Boosting.
Summary.

Taught by

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