15.0621 Data Mining: Finding the Data and Models that Create Value


Class Info

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. Students taking graduate version complete additional assignments.

This class has 15.075 as a prerequisite.

15.0621 will be offered this semester (Fall 2017). 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 15.0621 Class Site site or on the 15.0621 Stellar site.

Required Textbooks
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MIT 15.0621 Data Mining: Finding the Data and Models that Create Value Related Textbooks
MIT 15.0621 Data Mining: Finding the Data and Models that Create Value On The Web

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