Neural Designer 1.1.0 Details

Neural Designer is a professional application for predictive analytics that uses neural networks, which are mathematical models of brain functions that can be trained in order to perform certain tasks. These tasks are being used to solve function regression and pattern recognition problems. This software highlights functionality, usability and performance.

Publisher Description

Neural Designer is an advanced tool which makes intelligent use of data by discovering complex relationships, recognizing unknown patterns or predicting actual trends. This software highlights functionality, usability and performance. It is an innovative implementation of neural networks, the most used machine learning algorithms, which are mathematical models of the brain function that can be trained in order to perform certain tasks. Neural Designer contains a user interface as well, which has been conceived for simplifying data entry without having to program in order to solve problem. Neural designer outstands in performance, the amount of useful work accomplished by a system compared to the time and resources used. This has been achieved because Neural Designer has been created using the C++ programming language, which provides excellent results in terms of execution speed and memory allocation. Neural Designer is composed of three executable files, which are the different parts of the program joined by a user interface conceived for simplifying use. - Neural Designer Editor: it refers to the program module where you can choose what type of problem will be solved (regression or pattern recognition), enter data and do the tests to get the corresponding predictive model. - Neural Designer Engine: it is where all the mathematical operations selected in the previous module are done. - Neural Designer Viewer: it is the file where all the analysis results conducted by Neural Designer Editor are shown with its corresponding explanation. Neural Designer is able to guarantee the best possible results by offering innovative model selection techniques, comprehensive feedback in the design process and high computational performance.

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