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Description
D4M: Signal Processing on Databases (Fall 2012, MIT OCW). Instructor: Dr. Jeremy Kepner. D4M is 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. (from ocw.mit.edu)
Course Curriculum
- Lecture 0 – Introduction Unlimited
- Demo 0 – Introduction: Examples Demonstration Unlimited
- Lecture 1 – Using Associative Arrays Unlimited
- Demo 1 – Using Associative Arrays: Examples Demonstration Unlimited
- Lecture 2 – Group Theory Unlimited
- Demo 2 – Group Theory: Examples Demonstration Unlimited
- Lecture 3 – Antity Analysis in Unstructured Data Unlimited
- Demo 3 – Antity Analysis in Unstructured Data: Examples Demonstration Unlimited
- Lecture 4 – Analysis of Structured Data Unlimited
- Demo 4 – Analysis of Structured Data: Examples Demonstration Unlimited
- Lecture 5 – Perfect Power Law Graphs Unlimited
- Demo 5 – Perfect Power Law Graphs: Examples Demonstration Unlimited
- Lecture 6 – Bio Sequence Cross Correlation Unlimited
- Demo 6 – Bio Sequence Cross Correlation: Examples Demonstration Unlimited
- Demo 65 – Accumulo and D4M (Demo only, no lecture) Unlimited
- Lecture 7 – Kronecker Graphs, Data Generation, and Performance Unlimited
- Demo 7 – Kronecker Graphs, Data Generation, and Performance: Examples Demonstration Unlimited
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