Learn how to build, plot, and interpret a confusion matrix using PyTorch in this 24-minute video tutorial. Explore techniques for locally disabling PyTorch gradient tracking and computational graph generation while using a neural network to obtain predictions for every sample in a training set. Gain insights into the FashionMNIST dataset and understand the training loop process. Follow along with code examples and practical demonstrations to enhance your skills in neural network programming and evaluation.