Calculus

Calculus, Machine Learning, Math

Understanding the Softmax Function Derivative

This article discusses the derivative of the softmax function, providing an introductory example suitable for readers with a basic understanding of single-variable calculus. It outlines the mathematical principles necessary for computing this derivative and presents a concise expression for the softmax function’s Jacobian matrix, showcasing its application in probability distributions.

The directional derivative.
Calculus, Machine Learning, Math

Understanding the Directional Derivative and the Gradient

1 Introduction Understanding how functions change in different directions is crucial in many fields. For example in the context of neural networks where gradients are used to update weights during the training process. In this article, we will explore the concepts of the directional derivative and the gradient, and we will demonstrate their relationship through

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