Deep Learning in Communication
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Follow on Instagram for UpdatesDeep Learning in Communication Syllabus — Unit-wise Content
The official GTU curriculum for Deep Learning in Communication (subject code 4726006) as prescribed for EACE · Semester 2 divides the course into 7 units, covering 40 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (4726006)Unit 1 UNIT-I
- Introduction: AI, ML and DL, Research Domain and industry applications
- Tools and technologies
- Perspective of deep learning
Unit 2 UNIT-II
- Fundamental Of Neural Network: Introduction
- Understanding the biological neuron
- Exploring the artificial neuron
- Early implementation of ANN, Types of w.e.f
- AY 2021-22 activation functions
- Architectures of neural network
- Learning process in ANN
Unit 3 UNIT- III
- Training Deep Neural Network: Introduction
- Mathematics behind backpropagation
- Deep L layer neural network
- Understanding of notion of forward and backward propagation in perspective of computation graph
- Initializing weights in neural network
- Mini batch and stochastic gradient descent
- Other optimization algorithms
- Normalization of inputs
Unit 4 UNIT-IV
- Computer Vision using Convolutional Neural Network: Introduction to computer vision
- Challenges faced by traditional ANN to work with image data
- Building blocks of convolutional neural network
- Building a convolutional neural network
- CNN architecture
Unit 5 UNIT- V
- Representation Learning: Introduction
- Autoencoder fundamentals
- Regularization of autoencoder
- Representation learning in text
- Traditional methods
- Word embedding
- Document embedding
Unit 6 UNIT-VI
- Sequence Based Models: Introduction to sequence data
- Recurrent neural network
- Long short term memory
- Gated recurrent units
- Bi-directional models
- Language modelling and sequence modelling
Unit 7 UNIT-VII
- Deep Learning Case Studies: Disease detection from chest X ray images
- Channel estimation using DL, Noise and PSNR prediction using DL, DL for indoor localization
- Recent Development in Deep Learning in Communication (Study from latest research papers from Scopus indexed/web of science journals
- 04 hours during laboratory hours) w.e.f
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