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Uedu Open / Mathematics of Big Data and Machine Learning
RES.LL-005

Mathematics of Big Data and Machine Learning

Dr. Jeremy Kepner, Dr. Vijay Gadepally | January IAP 2020
Business & Management Digital Business & IT Data Science, Analytics & Computer Technology Computer Science Data Science Engineering Business Data Mining
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CC BY-NC-SA 4.0
課程簡介
This course introduces the Dynamic Distributed Dimensional Data Model (D4M), a breakthrough in computer programming that combines graph theory, linear algebra, and databases to address problems associated with Big Data. Search, social media, ad placement, mapping, tracking, spam filtering, fraud detection, wireless communication, drug discovery, and bioinformatics all attempt to find items of interest in vast quantities of data. This course teaches a signal processing approach to these problems by combining linear algebraic graph algorithms, group theory, and database design. This approach has been implemented in software. The class will begin with a number of practical problems, introduce the appropriate theory, and then apply the theory to these problems. Students will apply these ideas in the final project of their choosing. The course will contain a number of smaller assignments which will prepare the students with appropriate software infrastructure for completing their final projects.
Course Information
SourceMIT 開放式課程
LanguageEnglish
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