Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism.
It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail. This second edition has been expanded to include additional chapters on using frequent pattern trees for Association Rule Mining, comparing classifiers, ensemble classification and dealing with very large volumes of data. Principles of Data Mining aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.
Suitable as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. Login to see store details. This course prepares students to understand and conduct research in this area, and to create new techniques and apply them in various application fields.
Engineering Design Statement: In this research oriented course, the instructor lectures on a series of information visualization topics. Students are expected to read and present research papers and do homework assignments.
For the project assignment students write a project proposal, meet with the instructor individually to discuss the project, write a report summarizing the results of the project and present the results to the class. Students are provided a variety of research opportunities, both through the SURF Summer Undergraduate Research Fellowships program and the required capstone project sequence.
The undergraduate degree equips students with the tools and knowledge necessary for a successful research, industrial, and entrepreneurial career in computing. Units used to fulfill the Institute Core requirements do not count toward any of the option requirements. Passing grades must be earned in a total of units, including all courses used to satisfy the above requirements.
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- Data Mining and Big Data Bibliography.
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Students interested in simultaneously pursuing a degree in a second option must fulfill all the requirements of the computer science option. Courses may be used to simultaneously fulfill requirements in both options.
However, it is required that students have at least 72 units of computer science courses numbered 80abc, 81abc, or and above that are not simultaneously used for fulfilling a requirement of the second option, i. In general, approval is contingent on good academic performance by the student and demonstrated ability for handling the heavier course load.