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About ccs355 Syllabus NNDL
This document outlines the syllabus for a course on Neural Networks and Deep Learning according to Anna University's 2023 regulations. The course objectives are to understand the basics of deep neural networks, associative memory networks, convolutional neural networks, and apply deep learning techniques. The syllabus is divided into 5 units that cover introduction to neural networks, unsupervised learning networks, third generation networks like CNNs, deep feedforward networks, and recurrent neural networks. The course outcomes are applying CNNs for image processing, understanding unsupervised networks, applying CNN variants, analyzing deep learning computations, and applying autoencoders and generative models.
Detailed Information
| Author: | ['Kali Moorthi'] |
|---|---|
| Publication Year: | 2024 |
| Pages: | 3 |
| Language: | English |
| Format: | |
| Price: | FREE |
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