Learning Machine-Learning with Weka (EN)

Overview

Goals

Problem published by: Eleni Koutsoni The aim of the problem is to introduce the student to the understanding of its basic algorithms of Machine Learning through the Waikato Machine Learning software suite Environment for Knowledge Analysis (WEKA). Through this suite, which contains a collection of visualization tools and algorithms for data analysis and predictive modeling, along with graphical user interfaces for easy access to these functions, students will acquire skills important for their involvement with Machine Learning.

Learning Objectives

At the end of the problem the student will be able to use Machine Learning methods such as, -data pre-processing -clustering -classification -regression -data visualization -feature selection, but without the need for knowledge of any programming language optimized for Machine Learning. In addition to that, it facilitates the transition of students from theory to practice through tools visualization provided by the WEKA Suite.

Context

This activity can be applied to study programs for Electricians Computer Engineers / Computer Science and Informatics Systems, in courses dealing with Data Science, Predictive Modeling and Data Mining and Analysis. The aims of these courses will be the education of students for the rapidly developing sector of Big Data.