dc.contributor.author | Kepner, Jeremy | |
dc.coverage.temporal | Fall 2012 | |
dc.date.accessioned | 2020-07-21T18:36:53Z | |
dc.date.available | 2020-07-21T18:36:53Z | |
dc.date.issued | 2012-12 | |
dc.identifier | RES.LL-005-Fall2012 | |
dc.identifier.other | RES.LL-005 | |
dc.identifier.other | IMSCP-MD5-796efd9c97dbf328be87fbe7cd9a203c | |
dc.identifier.uri | https://hdl.handle.net/1721.1/126284 | |
dc.description.abstract | 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. | en |
dc.language.iso | en-US | |
dc.rights | This site (c) Massachusetts Institute of Technology 2020. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. | en |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 Unported | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/ | * |
dc.subject | big data | en |
dc.subject | data analytics | en |
dc.subject | dynamic distributed dimensional data model | en |
dc.subject | D4M | en |
dc.subject | associate arrays | en |
dc.subject | group theory | en |
dc.subject | entity analysis | en |
dc.subject | perfect Power Law | en |
dc.subject | bio sequence correlation | en |
dc.subject | Accumulo | en |
dc.subject | Kronecker graphs | en |
dc.title | RES.LL-005 D4M: Signal Processing on Databases, Fall 2012 | en |
dc.title.alternative | D4M: Signal Processing on Databases | en |
dc.audience.educationlevel | Undergraduate | |
dc.subject.cip | 140903 | en |
dc.date.updated | 2020-07-21T18:37:10Z | |