Fuzzy Logic And Neural Networks

University of California, San Diego via Swayam

Overview

Discover the fascinating world of Fuzzy Logic and Neural Networks with our comprehensive course.

Course Highlights:

Introduction to fuzzy sets and comparison with crisp sets
Detailed discussion on terms and grammar of fuzzy sets with numerical examples
Explanation of fuzzy reasoning and fuzzy clustering principles, supplemented by numerical examples
Fundamentals of neural networks and various learning methods
In-depth coverage of multi-layer feed forward neural network, radial basis function network, self-organizing map, counter-propagation neural network, recurrent neural network, and deep learning neural network, with appropriate numerical examples
Methods for evolving optimized fuzzy reasoning tools and neural networks, demonstrated with numerical examples
Introduction to two popular neuro-fuzzy systems with solved examples
Course summary

Intended Audience: This course is designed for students from all engineering disciplines, researchers, and practicing engineers.

Prerequisites: None.

Industry Support: Supported by RDCIS, Ranchi; CMERI, Durgapur; Reliance Industries, Mumbai; C-DAC, Kolkata; and others.

University: University of California, San Diego

Provider: Swayam

Categories: Machine Learning Courses, Deep Learning Courses, Neural Networks Courses