Innovations in Machine Learning

Theory and Applications (Studies in Fuzziness and Soft Computing)

Publisher: Springer

Written in English
Cover of: Innovations in Machine Learning |
Published: Pages: 274 Downloads: 861
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Subjects:

  • Machine learning,
  • Artificial intelligence,
  • Computers,
  • Mathematics,
  • Computer Books: General,
  • Applied,
  • Artificial Intelligence - General,
  • Case-based Machine Learning Paradigms,
  • Computational Algorithms in Machine Learning,
  • Explanation-based Learning Paradigms,
  • Mathematics / Applied

Edition Notes

ContributionsDawn E. Holmes (Editor), Lakhmi C. Jain (Editor)
The Physical Object
FormatHardcover
Number of Pages274
ID Numbers
Open LibraryOL9056131M
ISBN 103540306099
ISBN 109783540306092

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Machine Learning for Absolute Beginners has been written and designed for absolute beginners. It opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing specific algorithms applied in machine learning, including their pros and cons.

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Machine learning – as well as deep learning, natural language processing and cognitive computing – are driving innovations in identifying images.