This particular project is my Final year Project that is built using Python and the framework used is Pytorch. This project uses Convolutional Neural Network (CNN) that is used for image processing. This project allows you to enter a handwritten form of math equation on a canvas and save it in an image format.Once we get input, it’ll be checked if the image specifications are as per the defined specification. This image will go to the Convolutional Neural Network Model and the already trained model will generate their equivalent LaTeX in a way that we'll get the LaTeX of the equation. LaTeX will be converted to Math Grammar Rules. These rules are used to generate an Abstract Syntax Tree (AST) via LaTeX Macros which extracts structural information from mathematical expressions given in LaTeX format. AST is used to convert mathematical expressions into Extensible Markup Language (XML). XML marks the basis of mathematical expressions being machine-readable. This XML Tree is encoded to Content Math Markup Language (CMML) via an algorithm. CMML produces semantic enrichments in web documents i.e. text analysis via the algorithm that searches the specific entities from XML schema. In addition, Presentation Math Markup Language (PMML) is also encoded on XML Tree alongside CMML. and is used to provide a better presentation so as to be searched on MIR. The MIR used in this case is called Math Search. It’ll do so by analyzing the syntactic (E.g. Textual) and Semantic (E.g. Structural) information of a mathematical expression that it got as CMML and bringing the instances of the equation which was initially passed as an input in the order of the weightage in descending order depending upon the number of times it was searched previously and list down all the results.