Abstract

Machine learning uses techniques from statistics, mathematics and computer science to make computer programs learn from data. It is one of the most popular fields of computer science and finds applications in multiple streams of data analysis such as classification, regression, clustering, dimensionality reduction, density estimation and many more. Some real-life applications are spam filtering, medical diagnosis, autonomous driving, recommendation systems, facial recognition, stock prices prediction and many more. The following image shows a basic flow of any machine learning task. Data is provided by a user to a machine learning algorithm for analysis.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• What is machine learning?
• Why is it useful?
• What are its different approaches?

Learning Objectives

• Provide the basics of machine learning and its variants.
• Learn how to do classification using the training and test data.
• Learn how to use Galaxy's machine learning tools.