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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the back-propagation algorithm for deep neural networks, including the initialization of weights, forward pass, pre-activations, post-activations, error terms, weight updates, and the use of activation functions. The slides also discuss the importance of locality and translational invariance in convolutional neural networks.
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