Application of machine learning in data processing

Abstract

The main objective of this thesis is to present the Machine learning(ML) techniques and their algorithms briefly; Chapter 1 outlines the introduction about ML and its branches and the main reason why statistical agencies should start exploring the use of machine learning techniques. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Chapter 2 outlines the analysis of the most popular algorithm that is Support Vector Machines, which has been used to solve classifi cation task under supervised learning. Chapter 3 describes the Result obtained from high energy and Diabetes dataset using the SVM algorithm, LibSvm is used to generate the results and plots. The watershed algorithm is used for image processing and finding the clusters in the diffraction pattern of a protein crystal. Last section covers the application of machine learning in the eld of science, medical science, social media and many more.