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Machine Learning

Welcome!

Machine Learning has become a mainstay in the battle with information overload and the preferred technology for exploring the science of Big Data. As research generates immense quantities of data, measured now in terabytes or petabytes, the requirement for machine processing has moved from the realm of the data processing specialist to that of sophisticated and intelligent data management and analysis tools that can be used by anybody. Science, Engineering, Arts and many other endeavors will increasingly rely on such machine learning tools.

Machine Learning Modules

To facilitate broader understanding of machine learning in a wide range of disciplines, this project gently and thoroughly introduces the concepts and techniques of machine learning to undergraduate level students, and the professors who teach them. This material, in the form of teaching and learning modules, enables courses in many disciplines to incoporate a little or a lot of relevant machine learning content. While the modules do not cover all possible machine learning concepts, they do provide a broad and accessible entryway into the field.

These modules are appropriate for those who are brand new to the idea of machine learning, for those with more background and experiences with the concepts, and everybody in between.

What to Expect

In this modules, you will discover ready-to-use teaching and learning material for a variety of Machine Learning topics, from an introductory to advanced level. The modules are organized by general category and by topic within those categories. Each module is crafted with the goal of providing exposure to Machine Learning topics in an accessible way for students and faculty in just about any discipline. Introductory modules are easily tackled by students with no technical background, while more advanced modules require some technical knowledge (which can be obtained in earlier modules).

Module Organization

Introduction and Background

Supervised Methods

Unsupervised Methods

Learning Tools

Here are some of the excellent learning tools available online that are used in one or more of these Machine Learning modules.

  • AIspace - learning tools for a variety of Artificial Intelligence and Machine Learning concepts written in Java and designed to run on any computer.
  • Tips for Running AIspace Tools - a handout we compiled with information on troubleshooting security issues when running AIspace tools.
  • AIspace Quiz - a short quiz we created that can be used to assess or motivate learning with AIspace.
  • Weka - a very powerful and feature-rich software packaage with a collection of machine learning algorithms built-in.

Data Sets for Machine Learning

This is a collection of pointers to data sets that can be used for Machine Learning education. Some of the data linked below is suitable for use in various learning modules. Any specific data used by modules will be specified in the descriptions of those modules.

Data Sets

UCI Summary of Data Sets By Application Area:
http://kdd.ics.uci.edu/summary.data.application.html

Data Software and News from Statistics Community:
http://lib.stat.cmu.edu/

Data For Evaluating Learning in Valid Experiments
http://www.cs.utoronto.ca/~delve/

Modules and materials created by the Machine Learning project