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ADAV1UC 1001 - Applied Data Analytics II

Description
The course focuses on data mining and machine learning algorithms for analyzing very large amounts of data. The emphasis will be on Map Reduce as a tool for creating parallel algorithms that can process very large amounts of data. Topics include: Frequent Itemsets and Association Rules; Near Neighbor Search in High Dimensional Data; Locality Sensitive Hashing (LSH); Dimensionality Reduction; Recommendation Systems; Clustering, Link Analysis; Large scale supervised machine learning; Data streams; Mining the Web for Structured Data; and Web Advertising. Class Notes: COURSE OPEN TO BACHELOR'S PROGRAM STUDENTS ONLYNO CLASS 3/20/20 - SPRING RECESS. Enrollment Requirements: Restriction for UC BA & BS Courses Prereq for ADAV1-UC 1001.
Credits
4
Recent Professors
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Recent Semesters
Spring 2021, Spring 2020, Spring 2019, Spring 2018
Offered
Th, F, Tu
Avg. Sections
1