Lecture

Deep Learning: Backward Propagation and Vanishing Gradient

In course

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Description

This lecture covers the process of backward propagation in deep learning, focusing on the vanishing gradient problem. It explains the steps involved in updating weights through backpropagation and highlights the challenges faced due to the diminishing gradient effect. The instructor emphasizes the importance of avoiding linearity issues in the forward pass and the significance of hidden units that facilitate successful forward and backward passes.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_thvp984g

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

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