Reinforcement Learning and Deep RL Python Theory and Projects - DNN Activation Functions in PyTorch

The video tutorial covers activation functions in neural networks, focusing on sigmoid and ReLU functions. It explains how these functions work, their properties, and how to implement them using the torch library. The tutorial also introduces the concept of writing custom activation functions and provides a brief overview of loss functions, setting the stage for further exploration in the next video.

Explain the process of defining your own activation function in PyTorch.

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