Calculus Archive

Calculus For Machine Learning and Data Science

This series of blog posts introduces multivariate calculus for machine learning. While the first few posts should be accessible to anyone with a high-school math background, the articles covering vector calculus require a basic understanding of linear

The Fundamental Theorem of Calculus and Integration

In this post, we introduce and develop an intuitive understanding of integral calculus. We learn how the fundamental theorem of calculus relates integral calculus to differential calculus. Integration is the reverse operation of differentiation. Together they form

Lagrange Multipliers: An Introduction to Constrained Optimization

In this post we explain constrained optimization using LaGrange multipliers and illustrate it with a simple example. Lagrange multipliers enable us to maximize or minimize a multivariable function given equality constraints. This is useful if we want

Understanding The Gradient Descent Algorithm

In this post, we introduce the intuition as well as the math behind gradient descent, one of the foundational algorithms in modern artificial intelligence. Motivation for Gradient Descent In many engineering applications, you want to find the

Linearization of Differential Equations for Approximation

In this post we learn how to build linear approximations to non-linear functions and how to measure the error between our approximation and the desired function. Given a well-behaved higher-order function, we can find an approximation using

Power Series: Understand the Taylor and MacLaurin Series

In this post, we introduce power series as a method to approximate unknown functions. We derive the Maclaurin series and the Taylor series in simple and intuitive terms. Differential calculus is an amazing tool to describe changes

The Multivariable Chain Rule

In this post we learn how to apply the chain rule to vector-valued functions with multiple variables. We’ve seen how to apply the chain rule to real number functions. Now we can extend this concept into higher

The Hessian Matrix: Finding Minima and Maxima

In this post, we learn how to construct the Hessian matrix of a function and find out how the Hessian helps us determine minima and maxima. What is a Hessian Matrix? The Jacobian matrix helps us find

The Jacobian Matrix: Introducing Vector Calculus

We learn how to construct and apply a matrix of partial derivatives known as the Jacobian matrix. In the process, we also introduce vector calculus. The Jacobian matrix is a matrix containing the first-order partial derivatives of

How to Take Partial Derivatives

We learn how to take partial derivatives and develop an intuitive understanding of them by calculating the change in volume of a cylinder. Lastly, we explore total derivatives. Up until now, we’ve always differentiated functions with respect