Neural Networks (AI) Projects & Tutorials

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Monthly Tutorial Basics

$5
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Access to application description, downloadable source code, and basic instructions for setting up and building the Neural Network solution.
  • Documentation, Source Code

Monthly Tutorial Deluxe

$10
per month
You will have access to the same as Tier 1 and also the following:
– Access to videos of:
  • the application and solution code walk-throughs,
  • with detailed explanations of the Neural Network training and test data setup processing,
  • how to learn from the training sessions and improve performance, etc.
  • Documentation, Source Code
  • Code Walk-Through and Explanation Videos

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About Neural Networks (AI) Projects & Tutorials


What are Neural Networks?

They are a type of Artificial Intelligence (AI) that is constructed in a form that is somewhat similar to the human brain with “artificial” neurons interconnected with other neurons - the overall connection mapping between neurons contains the “memory” and “understanding” of how to work a particular application.

Neural Networks are used in “Deep Learning” algorithms which consist of Neural Networks that contain many layers of neurons. However, for these tutorials, we will strictly be working with simple Neural Networks that are at most a few layers in size with just a few neurons in each layer. You would be amazed at what they can accomplish.

For example, this unmanned helicopter was under semi-autonomous Neural Network guidance and control and only used several Neural Networks with just two middle layers.  I designed / coded / tested the entire flight control system software for this aircraft. In this case the Neural flight control system was not designed: 1) to handle sling loads, a very nonlinear dynamic disturbance to the helicopter (ask any pilot how difficult this maneuver is to do), or 2) to handle gusting / turbulent winds. However, the Neural Control System (with only two middle layers) adapted far beyond its training envelope and stabilized the helicopter while it carried sling loads and endured gusting winds as seen in the video.

Throughout my career I've seen Neural Networks do amazing things that I never anticipated when initially designing them for a particular application.  And that's why they have intrigued me and fueled my passion for all of their potential.

Why would I be interested in this topic?

If you are interested in the field of Artificial Intelligence (specifically Supervised Feed-Forward Neural Networks) and the applications –  and fall into one of two categories:

  • You are a software developer that wants to get her / his hands dirty (like a mechanic working on a car) and make an application work – and learn the tricks of the trade.
or

  • You are a casual observer and would like to observe how AI solutions for various applications come together.

Note that this approach does not use “Deep Learning” methods and algorithms. Instead it uses fundamental Neural Network techniques to build a superior solution for specific applications. The tutorials will show how to create and analyze the training and test data set, how to scale the data when applicable, how train the Neural Network and test the results, and how to use the latter step as a feedback loop to improve your system performance (e.g. improve the data sets).

What's in it for me?

You will learn the basics, and some advanced techniques (such as Performance Shaping), for the entire process of starting with an application, designing the Neural Network solution, and building & testing the Neural Network solution.

At the Tier 1 level, you will have access to the application description, downloadable source code, and basic instructions for setting up and building the Neural Network solution.

At the Tier 2 level, you will have access to the same as Tier 1 and also the following:
– Access to videos of:
  • the application and solution code walk-throughs,
  • with detailed explanations of the Neural Network training and test data setup processing,
  • how to learn from the training sessions and improve performance, etc.
Examples of my style of these kinds of videos can be seen in my Neural Network tech blog article and my Java WorldWind tech blog article.

What software development tools are required?

All of the required software tools are free - Octave, Java, (and in the future, Python).  Matlab runs are shown but Matlab is not required as the software is primarily designed for Octave.  However, if you are a high school or university student (or you teach in academia) then you can obtain a Matlab license for a very low cost.

The Neural Network learning / training algorithm is the Pyrenn Library's Levenberg-Marquardt optimization algorithm - the basic Pyrenn library (for Matlab / Octave or Python) can be obtained here.

So if you don’t have Matlab, you can download Octave for free from this link - GNU Octave Site.

The Integrated Development Environment (IDE) tools used for these projects include: NetBeans (Oracle 8.2 or Apache 11.0), IntelliJ IDEA, and Octave IDE.  The Matlab IDE will be used for demonstration purposes (for those that prefer to use Matlab).

What is your technical background?

I’m an Aerospace Engineer / Software Developer with 33 years of experience.  The languages that I've developed in include Java, C++, JavaScript, Matlab, Python, C, HTML5, Pascal, Ada, and FORTRAN.  I've worked various AI projects of all types (simulation, real time systems, prediction, etc.) since 1990.

The following is a list of interesting (fun) projects that I've worked on:

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