Alyuda Forecaster XL

Alyuda Forecaster XL is a forecasting Excel add-in, based on neural networks.
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Alyuda Forecaster XL Ranking & Summary

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  • Rating:
  • License:
  • Shareware
  • Price:
  • Free to try
  • Publisher Name:
  • By Alyuda Research
  • Publisher web site:
  • http://www.alyuda.com/
  • Operating Systems:
  • Windows 95, Windows 2000, Windows 98, Windows Me, Windows, Windows XP
  • Additional Requirements:
  • Windows 95/98/Me/2000/XP, Microsoft Excel 2000
  • File Size:
  • 1.5 MB
  • Total Downloads:
  • 3516

Alyuda Forecaster XL Tags


Alyuda Forecaster XL Description

Alyuda Forecaster XL is a forecasting Excel add-in, based on neural networks. It is the obvious choice for users, who need a reliable and easy-to-learn forecasting neural network tool embedded into the familiar MS Excel framework. Forecaster XL allows you to use neural networks for forecasting and classifications directly inside your Excel worksheets. You can instantly apply the capabilities of neural network forecasting to XLS data, while retaining all the data manipulation tools in Excel. Forecaster XL is designed specifically to save you time and money. It is reliable due to the implementation of the cutting-edge advances in Artificial Intelligence and ANN combined with proven neural network forecasting techniques. This forecasting neural network add-in is extremely easy to use for non-technical people. You only need to show your data and click just one button to prepare a forecasting neural network in Excel tailored to solve your specific problem. Forecaster XL is the only forecasting Excel add-in with an automatic neural network architecture and parameters selection. It gives you access to breakthrough algorithms for automatic data preprocessing and neural network preparation inside MS Excel. With these algorithms, you do not need to have any prior experience in statistics or artificial intelligence to exploit the power of neural networks in Excel. These algorithms make your data suitable for a neural network, select the most appropriate architecture and prepare the forecasting neural network for solving your problem.


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