Handwritten math equation solver using machine learning.

In the digital era, most of the human work is now been performed using the computer system. The computer's capacity to detect and understand meaningful Handwriting input from sources such as touch screens, pictures, paper documents, and other sources is referred to as handwriting character recognition. The diversity in people's handwriting style increases the complexity of handwritten characters. Also, grading academic answer sheets manually and providing an unbiased genuine grade is a challenging task. The aim of the work is to create handwriting character recognition system that will be used to read handwriting notes and solve mathematical equations. The ultimate goal is to show that neural networks can solve equations from a handwritten source effectively. In this paper, we present a web application-based equation solver that uses a camera image of an equation to display the solution. The program has the ability to solve simple arithmetic equations (addition, subtraction, multiplication) and up to two systems of linear equation variables handwritten or typed in a computer font. [ABSTRACT FROM AUTHOR]