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.

 

NeuroSolutions for Excel
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Tag the Data

Before training a neural network you need to partition the columns and the rows of your spreadsheet. Each column used by the neural network can either be tagged as an input or a desired output. The rows are then segmented into one or more of the following four groups:
  • Training - Data used by the neural network to learn from.
  • Cross Validation - Data used to evaluate the performance during the learning process to avoid over-training.
  • Testing - Data used to evaluate the performance after the training is complete.
  • Production - Input data to feed into the trained neural network to produce an output.

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