Multimedia and Data Mining

Course ID 15826

Doctoral Breadth Course: Software Systems - (-)
Classes marked with a "-" (dash) are intended as more advanced topics for CSD doctoral and 5th year master's students in the specific research area.

Description

The course covers advanced algorithms for learning, analysis, data management and visualization of large datasets. Topics include indexing for text and DNA databases, searching medical and multimedia databases by content, fundamental signal processing methods, compression, fractals in databases, data mining, privacy and security issues, rule discovery, data visualization, graph mining, stream mining.

Key Topics
Advanced algorithms for learning, analysis, data management and visualization of large datasets

Required Background Knowledge
intro DB course (b-trees, hashing), or permission of instructor.

Course Relevance
CSD phd; CSD MSc; SCS phd; other phd students, with instructors permission.

Course Goals
Familiarity with advanced tools for large data analytics.

Learning Resources
python3 (scikit-learn); lecture slides of instructor; pdf of textbooks and of key research papers.

Assessment Structure
midterm 20%; homeworks 10%; project 40%; final 30%

Course Link
https://www.cs.cmu.edu/~christos/courses/826.F25/syllabus.html

Instructor(s)