Learn Neural Networks using Matlab Programming
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Learn Neural Networks using Matlab Programming

Learn Neural Networks Fundamentals, using Matlab NN toolbox with multiple programming examples included !
2.5 (31 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1,326 students enrolled
Last updated 12/2016
Current price: $10 Original price: $95 Discount: 89% off
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  • 2 hours on-demand video
  • 1 Article
  • 8 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What Will I Learn?
Work the Neural Network toolbox in Matlab
Analyze, design, and optimize Neural Networks in Matlab Toolbox
Understand the design, and infrastructures of Neural Networks
View Curriculum
  • Matlab Programming - This course is also available for download
  • Matlab ( MAC & Windows ) Supported

This course offers Coursovie Training Certificate in addition to Udemy Certificate. Coursovie Certificate is FREE and requires registration on Coursovie Website. 

Introduction :

MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language developed by MathWorks. Although MATLAB is intended primarily for numerical computing, but by optional toolboxes, using the MuPAD symbolic engine, has access to symbolic computing capabilities too. One of these toolboxes is Neural Network toolbox. This toolbox is free, open source software for simulating models of brain and central nervous system, based on MATLAB computational platform. In these courses you will learn the general principles of Neural Network Toolbox designed in Matlab and you will be able to use this Toolbox efficiently as well.

The list of contents is:

Introduction – in this chapter the Neural Network Toolbox is Defined and introduced. An overview of neural network application is provided and the neural network training process for pattern recognition, function fitting and clustering data in demonstrated.

Neuron models – A description of the neuron model is provided, including simple neurons, transfer functions, and vector inputs and single and multiple layers neurons are explained. The format of input data structures is very effective in the simulation results of both static and dynamic networks. So this effect is discussed in this chapter too. And finally the incremental and batch training rule is explained.

Perceptron networks – In this chapter the perceptron architecture is shown and it is explained how to create a perceptron in Neural network toolbox. The perceptron learning rule and its training algorithm is discussed and finally the network/Data manager GUI is explained.

Linear filters – in this chapter linear networks and linear system design function is discussed. The tapped delay lines and linear filters are discussed and at the end of the chapter LMS algorithm and linear classification algorithm used for linear filters are explained.

Backpropagation networks – The architecture, simulation, and several high-performance backpropagation training algorithms of backpropagation networks are discussed in this chapter.

Conclusion – in this chapter the memory and speed of different backpropagation training algorithms are illustrated. And at the end of the chapter all these algorithms are compared to help you select the best training algorithm for your problem in hand.

Matlab Software Installation: You are required to install the Matlab Software on your machine, so you can start executing the codes, and examples we work during the course.

What am I going to get from this course?

At the end of this course you are a confident Matlab Programmer using the Neural Network Toolbox in a proper manner according to the specific problem that you want to solve.

In this course you will learn some general and important network structures used in Neural Network Toolbox.

By the end of the course, you are familiar with different kinds of training of a neural networks and the use of each algorithm. You will learn how to modify your coding in Matlab to have the toolbox train your network in your desired manner.

At the end, different types of training algorithm are compared using some benchmarks to show the ability of each algorithm and at the same time to provide good examples that the student can use for more practice.

At last you are fully able to solve any engineering and technical Neural Network project offered at University or College

Who is the target audience?
  • Engineers, Students, and Researchers interested in Neural Networks
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Curriculum For This Course
Expand All 26 Lectures Collapse All 26 Lectures 02:07:41
How to Request your Coursovie Certificate
2 Lectures 05:07
Chapter 2
4 Lectures 22:26
Simple Neuron

Network architecture

Data structure

Training style
Chapter 3
3 Lectures 19:21
Neuron Model

Perceptron networks

GUI nntool
Chapter 4
2 Lectures 10:35
Network architecture

Linear filters & linear classification
Chapter 5
7 Lectures 34:40
Introduction to Training Process

Back Propagation Architecture


Faster learning_Heuristic algorithm

Faster training-numerical optimization techniques

Numerical techniques_Quasi newton

Numerical techniques_Levenberg_Marquart
Chapter 6
2 Lectures 13:15
Comparison of different training algorithms

Last Word
1 Lecture 00:00
2 pages
About the Instructor
Coursovie Training Inc. Hossein Tootoonchy
4.3 Average rating
797 Reviews
7,770 Students
5 Courses
Invest in yourself, Join 7000 students in the community.

I'm Hossein Tootoonchy. I've started 4 businesses in the past 4 years. I grew my last company to over $160,000 in revenue before selling it while I was a freshman at College. More recently, I've been helping over 55000 monthly readers find business ideas and turn them into profitable companies. In the process, I've worked with thousands of entrepreneurs who want to learn how to start a business the right way. I've become a pro at both launching my own new businesses and coaching others on how to do the same. This won't be easy, but am sharing all I've learned, so you can find the business idea that is right for you too. 

I am the founder of Coursovie Training Inc. which specializes in teaching technical courses in engineering field. Coursovie stands for Course + Movie, where ,my colleagues and I teach engineering courses using videos to reach thousands students. Coursovie's mission is to teach the engineering fundamentals practically, and working with passionate people. It is a journey and we are proud to be a part of it. Coursovie Training Inc. is an American New Start up that offers an ever growing range of high quality trainings in engineering and business fields.

All the trainings are produced by experts with the passion for teaching. All the examples introduced during the videos are based on the industry need, and cover the foundation of the engineering discipline under study.