Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01v979v5693
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Verma, Naveen | - |
dc.contributor.author | Ashraf, Ammad | - |
dc.date.accessioned | 2017-07-24T13:02:55Z | - |
dc.date.available | 2017-07-24T13:02:55Z | - |
dc.date.created | 2017-05-08 | - |
dc.date.issued | 2017-5-8 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01v979v5693 | - |
dc.description.abstract | Machine learning allows for us to interact with data in a meaningful way on a very large scale. A the amount data available to us grows, so does the potential of machine learning. However, there is a drawback in that the computations needed to draw conclusions from this data can be extremely expensive. This paper explores a potential use of a machine learning accelerator that allows us to do these computations in a more efficient manner. | en_US |
dc.language.iso | en_US | en_US |
dc.title | Sound Sensing System Using Machine Learning Accelerator | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2017 | en_US |
pu.department | Electrical Engineering | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 960897978 | - |
pu.contributor.advisorid | 960474920 | - |
Appears in Collections: | Electrical Engineering, 1932-2020 |
Files in This Item:
File | Size | Format | |
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Ashraf_Ammad.pdf | 876.69 kB | Adobe PDF | Request a copy |
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