Lecture

Training Neural Networks

In course

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Description

This lecture covers the training of neural networks using stochastic gradient descent, chain rules for forward and backward propagation, computation of gradients with respect to parameters, weight decay, and the concept of dropout to prevent overfitting by randomly dropping subsets of units in the network.

Official source

https://mediaspace.epfl.ch/media/0_eohffs2c

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

Physics

Nuclear physics: Topics in nuclear physics

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