Go Back   2023 2024 Courses.Ind.In > Main Category > Main Forum

  #1  
Old January 14th, 2021, 10:58 AM
Super Moderator
 
Join Date: Aug 2012
Default Sathyabama Institute of Science and Technology BE CSE SCSA3015 Deep Learning Syllabus

Sathyabama Institute of Science and Technology BE CSE SCSA3015 Deep Learning Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF COMPUTING

SCSA3015 DEEP LEARNING
L T P Credits Total Marks
3 0 0 3 100

UNIT 1 INTRODUCTION 9 Hrs.
Introduction to machine learning- Linear models (SVMs and Perceptrons, logistic regression)- Intro to Neural Nets: What a
shallow network computes- Training a network: loss functions, back propagation and stochastic gradient descent- Neural
networks as universal function approximates.

UNIT 2 DEEP NETWORK 9 Hrs.
History of Deep Learning- A Probabilistic Theory of Deep Learning- Backpropagation and regularization, batch
normalization- VC Dimension and Neural Nets-Deep Vs Shallow Networks- Convolutional Networks- Generative Adversarial
Networks (GAN), Semi-supervised Learning.

UNIT 3 DIMENTIONALITY REDUCTION 9 Hrs.
Linear (PCA, LDA) and manifolds, metric learning - Auto encoders and dimensionality reduction in networks - Introduction to
Convnet - Architectures – AlexNet, VGG, Inception, ResNet - Training a Convnet: weights initialization, batch normalization,
hyper parameter optimization.

UNIT 4 OPTIMIZATION AND GENERALIZATION 9 Hrs.
Optimization in deep learning– Non-convex optimization for deep networks- Stochastic Optimization- Generalization in
neural networks- Spatial Transformer Networks- Recurrent networks, LSTM - Recurrent Neural Network Language Models-
Word-Level RNNs & Deep Reinforcement Learning - Computational & Artificial Neuroscience

UNIT 5 CASE STUDY AND APPLICATIONS 9 Hrs.
Imagenet- Detection-Audio WaveNet-Natural Language Processing Word2Vec - Joint Detection- BioInformatics- Face
Recognition- Scene Understanding- Gathering Image Captions.
Max.45 Hrs.

COURSES OUTCOMES
On completion of the course, student will be able to
CO1 - Understand basics of deep learning.
CO2 - Implement various deep learning models.
CO3 - Realign high dimensional data using reduction techniques.
CO4 - Analyze optimization and generalization in deep learning.
CO5 - Explore the deep learning applications.
CO6 - Design and creation of data models.

TEXT / REFERENCE BOOKS
1. Cosma Rohilla Shalizi, Advanced Data Analysis from an Elementary Point of View, 2015.
2. Deng and Yu, Deep Learning: Methods and Applications, Now Publishers, 2013.
3. Ian Good fellow, Yoshua Bengio, Aaron Courville, Deep Learning, MIT Press, 2016.
4. Michael Nielsen, Neural Networks and Deep Learning, Determination Press, 2015.

END SEMESTER EXAMINATION QUESTION PAPER PATTERN
Max. Marks : 100 Exam Duration : 3 Hrs.
PART A : 10 Questions of 2 marks each-No choice 20 Marks
PART B : 2 Questions from each unit with internal choice, each carrying 16 marks 80 Marks
Reply With Quote Quick reply to this message
Reply
Similar Threads
Thread
Sathyabama Institute of Science and Technology B.E. - Automobile Engineering SBMA4007 Forensic Science Syllabus
Sathyabama Institute of Science and Technology LL.B - LL.B SAL1753 Intellectual Property Law Syllabus
Sathyabama Institute of Science and Technology BE CSE SITA1301 Programming in Java Syllabus
Sathyabama Institute of Science and Technology B.Tech - Chemical Engineering SCHA3004 Fertilizer technology Syllabus
Sathyabama Institute of Science and Technology LL.B - LL.B SALA4001 Intellectual Property Law Syllabus
Nirma University MTech - Computer Science and Engineering 16 3CS12D302 Deep Learning and Applications Syllabus
Sathyabama Institute of Science and Technology LL.B - LL.B SAL1903 Principles of Taxation Law Syllabus
Sathyabama Institute of Science and Technology BE ECE SECA1702 Wireless Communication Syllabus
Sathyabama Institute of Science and Technology BBA.LL.B - B.B.A.LL.B. (Honours) SAL1052 Transportation Law Syllabus
Sathyabama Institute of Science and Technology BBA.LL.B - B.B.A.LL.B. (Honours) SCSA4001 R Programming Syllabus
Sathyabama Institute of Science and Technology BE ECE SCHA4001 Corrosion Engineering Syllabus
Sathyabama Institute of Science and Technology B.Sc. Computer Science SBS1201 FUNDAMENTALS OF DATA STRUCTURES Syllabus
Sathyabama Institute of Science and Technology BE CSE SAIC4001 Industry 4.0 Syllabus
Sathyabama Institute of Science and Technology ME CSE SCSA7006 Machine Learning Syllabus
Sathyabama Institute of Science and Technology B.Sc. Computer Science SBS1611 ARTIFICIAL INTELLIGENCE Syllabus
Sathyabama Institute of Science and Technology B.E. - Mechanical Engineering Part Time SMEA1401 Manufacturing Technology - I Syllabus
Sathyabama Institute of Science and Technology BE CSE SCSA1302 Theory of Computation Syllabus
Sathyabama Institute of Science and Technology B.Com.LL.B - B.Com.LL.B. (Honours) SAEA4001 Fundamentals of Aerospace Technology Syllabus
Sathyabama Institute of Science and Technology B.E. - Automobile Engineering SAEA4001 Fundamentals of Aerospace Technology Syllabus
Sathyabama Institute of Science and Technology B.Sc. Computer Science SBS1604 SOFTWARE TESTING Syllabus


Quick Reply
Your Username: Click here to log in

Message:
Options



All times are GMT +5.5. The time now is 06:20 PM.


Powered by vBulletin® Version 3.8.7
Copyright ©2000 - 2024, vBulletin Solutions, Inc.
Search Engine Friendly URLs by vBSEO 3.6.1
vBulletin Optimisation provided by vB Optimise (Lite) - vBulletin Mods & Addons Copyright © 2024 DragonByte Technologies Ltd.