What are softmax functions in machine learning?

The softmax function is a mathematical function commonly used in machine learning, particularly in the output layer of classification models. It converts a vector of raw scores (logits) into probabilities, making each value range between 0 and 1 and ensuring that the total sum is 1. This allows the model to interpret the output as the probability of each class, making the softmax function essential for multi-class classification tasks. Softmax is widely used in neural networks, especially in natural language processing and image recognition problems.