Master PyTorch Fundamentals: From Tensors to Neural Network Layers

Most PyTorch practitioners operate the framework without understanding its underlying mechanics. This foundational series demystifies the five core concepts—tensor creation, mathematical operations, gradient computation, and activation functions—that power every neural network. Understanding these fundamentals enables developers to design models more effectively and troubleshoot deep learning systems with genuine comprehension.