An Empirical Analysis of ML Algorithms

Abstract

Machine learning makes it possible for machines to learn by themselves. It has a huge impact not just in automating the tasks for developers and IT professionals, but also affects most of the domains today. This includes healthcare, finance, marketing, security, automotive industries and many more .There isn’t an industry that is not looking up for machine learning and AI solutions today. In this work, an experimental analysis of few supervised and non supervised techniques such as kmeans, logistic regression, random forest and decision tree are done on text dataset and H1b data set to understand and visualize the results. The results are found satisfactory.