Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Activation Functions

The video tutorial introduces activation functions in the Torch library, focusing on sigmoid and ReLU functions. It explains how to define and use these functions with examples, and discusses the possibility of creating custom activation functions. The tutorial also briefly introduces loss functions, setting the stage for understanding their role in training neural networks using gradient descent.

Explain the process of defining your own activation function in the context of the Torch package.

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What is the significance of the loss function in training a neural network?

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