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, 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.
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.
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).
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.
UCI Summary of Data Sets By Application Area:
Data Software and News from Statistics Community:
Data For Evaluating Learning in Valid Experiments