Learn how to build a neural network for classification from scratch using PyTorch in this comprehensive 40-minute tutorial. Begin by understanding the fundamentals of neural networks and setting up your development environment with PyTorch 2.0. Explore data preparation techniques, including loading datasets and splitting them into training and validation sets. Dive deep into the process of creating tensors from data and constructing a neural network architecture. Gain insights into activation functions, particularly ReLU, and their role in neural network performance. Follow along with hands-on coding examples and practical explanations to master the essentials of building and implementing neural networks for classification tasks using PyTorch.