Explore ensemble learning techniques in this comprehensive video course on bagging and boosting. Dive into key concepts like bias and variance, ensemble methods, and the differences between bagging and boosting. Learn how to combine multiple algorithms to solve complex problems and improve overall performance in machine learning applications. Gain a solid foundation in these important techniques, essential for extracting maximum performance from large datasets. Perfect for working professionals looking to enhance their machine learning skills and advance their careers in data science, artificial intelligence, and related fields.
Overview
Syllabus
Introduction.
Agenda.
Bias and Variance.
Ensemble Methods.
Introduction to Bagging.
Bagging vs Boosting.
Summary.
Taught by
Great Learning
