Course Description

“Neural Network Made Easy : A practical approach with NeuroSolutions” is a one-day hands-on workshop that focus on fundamental concepts and techniques for analysis and design of neural computation as an approach to intelligent problem solving. A great feature of the course is that the teaching material will illustrate practical graphical neural network development tools (NeuroSolutions) that enable you to easily create a neural networks model from your data. The course also illustrate the process of building of neural network directly from Excel that simplifies and enhances the process of getting data into and out of a neural network.

Pre-requisites:
Candidtate must have experience with basic computer operations.

Course Outline:

√ Fundamental Principles of Neural Network
o Overview of neural network architectures and training
o When to use and why should you use neural network

√ Neural Network Simulation Environement using NeuroSolutions.
o Overview of Breadboards, palettes,families, etc.
o The Neural Wizard
o Overview of Multilayer Perceptron (MLP); Nonlinear extensions to linear adaptive systems
o Tips and tricks of the trade: Setting the MLP parameters
o Applications of MLPs
o Creating, training and testing the neural networks
o Using Probes on training process and results
o Setting of the network paramenters

√ Bulding Neural Network from Excel Data.
o Preprocessing and analyzing your input data.
o Data Tagging
o Creating the neural network
o Training the neural network
o Testing the neural network
o Analyzing your results
o Optimizing the neural network paramenters / inputs

Who Should Attend
Engineer, researchers and scientists who want to sharpen their fundamentals understanding of the basic idea of neural network concepts and methodology and learn how to design and build neural network with a graphical neural network development tool to solve real-world problems.

Course Benefits
Upon the completion of the course, the participants should be able to understand the basic concepts and principles of AI neural networks. They should also be able to design a neural network to solve a particular problem.