Foundations of Deep Learning
Massachusetts Institute of Technology
This course aims to provide a comprehensive tutorial and survey about the recent advances towards enabling the efficient processing of deep learning. Specifically, it will provide an overview of deep learning, discuss various hardware platforms and architectures that support deep learning, and highlight key trends in recent efficient processing techniques that reduce the cost of computation for deep learning either solely via hardware design changes or via joint hardware design and network algorithm changes. It will also summarize various development resources that can enable researchers and practitioners to quickly get started on deep learning design, and highlight important benchmarking metrics and design considerations that should be used for evaluating the rapidly growing number of deep learning hardware designs, optionally including algorithmic co-design, being proposed in academia and industry.
Location | Hong Kong |
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Period |
10 Oct 2018
- 10 Oct 2018
|
level | PhD |
Credits | None |
Program fee | 500 USD |
Accommodation | Not offered |
Application deadline | 9 October 2018 |
Entry requirements | None |
Contact information: |