KB – Neural Data Mining with Python sources


The aim of this book is to present and describe in detail the algorithms to extract the knowledge hidden inside data using Python language, which allows us to read and easily understand the nature and the characteristics of the rules of the computing utilized, as opposed to what happens in commercial applications, which are available only in the form of running codes, which remain impossible to modify.

The algorithms of computing contained within the book are minutely described, documented and available in the Python source format, and serve to extract the hidden knowledge within the data whether they are textual or numerical kinds. There are also various examples of usage, underlining the characteristics, method of execution and providing comments on the obtained results.

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Python sources: http://www.freeopen.org/?p=73

Examples: http://www.freeopen.org/?p=89

KIndex: http://www.freeopen.org/?p=213

Know4Business - Neural Data Mining in Google App Engine - Tutorial

Know4Business in GAE Cloud provides six tools:

  • SOURCE to acquire and maintain records to process available in tabular form
  • CATALOGUE to catalog the sources, with an algorithm based on the theory of neural networks (Kohonen)
  • STATISTICS to perform statistical analysis, to explore the goodness of classification, in addition to the results of the cataloging function (see SHOW)
  • CLASSIFIER to classify new entities "on the fly", using the training matrix function obtained from the previous catalog
  • SHOW   to   view   the   reports,   analytical   and   descriptive   summary   of   the   groups   created   by   cataloging   and classification
  • CHART that displays a vertical bar graph in the CV (coefficient of variation) of the variables / columns of the identified groups

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