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About Neural Networks PDF
This document provides an overview of a deep learning course at UVA. It outlines: - Prerequisites for the course including calculus, linear algebra, probability, statistics, programming, and patience. - An overview of topics covered in the course including training deep learning models, neural networks for computer vision, natural language, unsupervised learning, and reinforcement learning. - Logistics of the course including lectures, labs, assignments, and a final exam making up the grading. Labs involve practical assignments in Python and Tensorflow. - Information about the instructors and TAs, as well as resources like the course website and virtual classroom. - An overview of the first lecture covering applications of
Detailed Information
| Author: | ['Ikshwak'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 89 |
| Language: | English |
| Format: | |
| Price: | FREE |
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