Deep Learning - Computer Vision for Beginners Using PyTorch - Building the First Neural Network

The video tutorial explains how to build a deep neural network using the Torch library. It covers the structure of a neural network, including input, hidden, and output layers, and the use of activation functions like Relu and sigmoid. The tutorial also demonstrates how to define a model and loss function in PyTorch, and how to implement the model using PyTorch's torch.nn and torch.optim packages. The process of stacking layers in a sequential model and applying linear operations and activation functions is detailed, along with the use of optimization methods like stochastic gradient descent.

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