Optimizing Multi-Class Classification: Softmax and Cross-Entropy Loss in PyTorch
Purpose: In multi-class classification, where a model predicts one class from multiple possibilities (e.g., classifying handwritten digits in MNIST), softmax takes a vector of unbounded real numbers as input and transforms them into a probability distribution