Lecture

Bagging: Regularization Method in Deep Learning

In course

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Description

This lecture covers the concept of bagging as a regularization method in deep learning, where multiple variants of a model are trained on different subsets of data to improve generalization. The instructor explains the bagging algorithm, how each model can be a deep network, and how the models see different data sets. The lecture also includes a quiz on the benefits of averaging predictions over multiple models in machine learning competitions.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_xdtyns6q

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

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