NeuroSolutions for Excel is a Microsoft Excel add-in that simplifies and enhances the process of getting data into and out of a NeuroSolutions neural network. This tool benefits both the novice and the advanced neural network developer by offering easy to use, yet extremely powerful features. The foremost feature of this product is that all tasks can be performed directly from Excel!
The Custom Solution Wizard does more than just create an isolated DLL. It integrates the DLL into a working sample application, giving you an excellent starting point for your own application. Sample applications can be created for Visual Basic, Access, Excel, Visual C++ and Active Server Pages (ASP web pages). In addition, you can also use the CSW to develop custom neural network models for our financial analysis product, TradingSolutions.
The NeuroSolutions for MATLAB neural network toolbox is avaluable addition to MATLAB's technical computing capabilities allowing users to leverage the power of NeuroSolutions inside MATLAB. The toolbox features 15 neural models, 5 learning algorithms and a host of useful utilities integrated in an easy-to-use interface, which requires "next to no knowledge" of neural networks to begin using the product.
“Introduction to Neural Network: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.
TradingSolutions is a software product that helps you make better trading decisions by combining traditional technical analysis with state-of-the-art artificial intelligence technologies. Use any combination of financial indicators in conjunction with advanced neural networks and genetic algorithms to create trading models that are remarkably effective.

 


Customer Interviews:

Cameron Cooper - Enhancing Education for Future Generations!

Cameron Cooper has been a instructor at Fort Lewis College in Southwestern Colorado for 4-years teaching developmental mathematics and computer science and also serves as an enrollment analyst. Mr. Cooper has an extensive educational background with a Bachelors in Mathematics from Occidental College, a Masters in Information Networking from Carnegie Mellon University, a Masters in Communications from Northwestern University and a Masters in Education from Harvard University. Mr. Cooper is a doctoral candidate in Applied Management & Decision Sciences at Walden University.

Mr. Cooper has been using NeuroSolutions and NeuroSolutions for Excel for the past 2-years and has attended NeuroDimension's Neural Network Course. AT-RISK identifies "at risk" students for Developmental Mathematic courses, which have an average nationwide failure rates between 40% and 50% . AT-RISK uses various input factors such as learning styles, responses to questions about attitudes & beliefs regarding mathematics, high school GPA and standardized test scores to determine whether the student should take the support class designed around AT-RISK. The support class is 1-hour per week and it addresses frustration tolerance, test anxiety and much more. This class has increased the overall student success rate by 8% in the first semester compared to the previous year.

Fort Lewis College has already adopted the AT-RISK neural network application for future semesters and is looking at implementing it for other problematic courses. In addition, Mr. Cooper has been approached by several other colleges to implement the AT-RISK project at their schools and he also has been approached by a national research organization for potential nationwide distribution.

The AT-RISK project uses a standard Multilayer Perceptron (MLP), single hidden-layer network with approximately 50 weights. The initial network was created with 70 inputs, trimmed to 20 using Spearman's Rho Correlation and refined again to 8 inputs using logistic regression. The final network used 6 inputs which was finalized using backwards elimination. Mr. Cooper used NeuroSolutions for Excel's Leave-N-Out Training feature to create a model that was 81% accurate in predicting "at risk" students.

Cameron had many great things to say about why he uses NeuroSolutions such as the "latitude in constructing neural networks" and that NeuroDimension "always incorporates the latest technologies" in NeuroSolutions. Mr. Cooper also described his experience with NeuroDimension's support and services as an "invaluable resource".

We would like to thank Mr. Cooper for sharing his success with NeuroSolutions and we hope to continue to see great things from Mr. Cooper and AT-RISK in the near future! If you are interested in contacting Mr. Cooper about the AT-RISK project, please email him at cooper_c -at- fortlewis.edu.

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