15.0621 Data Mining: Finding the Data and Models that Create Value
Provides an introduction to data mining and machine learning, a class of methods that assist in recognizing patterns and making intelligent use of massive amounts of data collected via the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, medical databases, search engines, and social networks. Includes topics in logistic regression, association rules, tree-structured classification and regression, cluster analysis, discriminant analysis, and neural network methods. Presents examples of successful applications in areas such as credit ratings, fraud detection, marketing, customer relationship management, and investments. Introduces data-mining software. Term project required. Meets with 15.062 when offered concurrently. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details.
This class has 15.075 as a prerequisite.
15.0621 will be offered this semester (Fall 2018). It is instructed by R. E. Welsch.
Lecture occurs 4:00 PM to 5:30 PM on Mondays and Wednesdays in E51-345.
This class counts for a total of 6 credits.
You can find more information at the http://www.google.com/search?&q=MIT+%2B+15.0621&btnG=Google+Search&inurl=https site.
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