Unit 1 Introduction

4 lecture hours

• Deep learning basics
• Applications: Discuss in detail
• Neural Network concepts

Unit 2 Neural Network

10 lecture hours

• Introduction of Neural Network
• Working of Neural Network
• Types of Neural Networks
• Activation function
• Deep Feed forward Network
• Neural Network - Use Case
• Applications of ANN, ANN vs BNN

Unit 3 Neural Network Based Fuzzy Systems

12 lecture hours

• Neural Realization of Basic Fuzzy Logic Operators
• Neural Network Based Fuzzy Logic Inference
• Neural Network Driven Fuzzy Reasoning
• Rule based Neural Fuzzy Modeling
• Neural Fuzzy Relational Systems
• Neuro Fuzzy Controllers
• Recent Applications

Unit 4 Introduction to Tensorflow, Tenserflow Basics, Transfer

10 lecture hours

• Optimization in Deep Learning
• Natural Language Processing basics

Unit 5 Deep Learning Algorithms

• CNN, LSTM, RNN, GAN, RBFN, MLP, SOM, DBN, RBM 12 25% Total Hours: 48 100% Textbook: 1
• "Machine Learning: A Probabilistic Perspective"
• The MIT Press
• "Introduction to Machine Learning”
• MIT Press
• Prentice Hall of India
• 3rd Edition 2014
• Semester: VI Subject Name: Deep Learning Principles and Practices Subject Code: 3174201 w.e.f. 2022-23 http://syllabus.gtu.ac.in/ Page no. 2 of 2 3
• A. "Deep Learning with TensorFlow: Explore neural networks with Python"
• Packt Publisher
• Rajasekaran and G.A
• Vijayalakshmi Pai, "Neural Networks
• Fuzzy Logic and Genetic Algorithms"
• PHI Learning Pvt