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Machine learning a guide to current research by

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Published by Kluwer Academic Publishers in Boston .
Written in English

Subjects:

  • Machine learning.,
  • Artificial intelligence.

Book details:

Edition Notes

Statementedited by Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski.
SeriesThe Kluwer international series in engineering and computer science ;, SECS 12
ContributionsMitchell, Tom M., 1951-, Carbonell, Jaime G., Michalski, Ryszard Stanislaw, 1937-
Classifications
LC ClassificationsQ325 .M318 1986
The Physical Object
Paginationxiv, 429 p. :
Number of Pages429
ID Numbers
Open LibraryOL2710095M
ISBN 100898382149
LC Control Number86002766

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This book didn't warrant the name Machine Learning. There are a total of 4 stories that have anything to do with the topic. It was a gross misrepresentation of the content of the book and that is almost as annoying as the fact that the Silo stories (which are in the book and after which the book could have been named) were far more interesting /5. Machine Learning is what drives AI. Experts in this domain are rare, employers fight for the ML-skilled talent. With this book, you will learn how Machine Learning works. A hundred pages from now, you will be ready to build complex AI systems, pass an interview or start your own business. All you need to know about Machine Learning in a hundred pages. Machine learning methods can be used for on-the-job improvement of existing machine designs. The amount of knowledge available about certain tasks might be too large. An MIT Press book Ian Goodfellow and Yoshua Bengio and Aaron Courville The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.

Packt is the online library and learning platform for professional developers. Learn Python, JavaScript, Angular and more with eBooks, videos and courses Packt | Programming Books, eBooks & . Understanding Machine Learning: From Theory to Algorithms By Shai Shalev-Shwartz and Shai Ben-David. Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. Understanding Machine Learning. Authors: Shai Shalev-Shwartz and Shai Ben-David. This book gives a structured introduction to machine learning. It looks at the fundamental theories of machine learning and the mathematical derivations that transform these concepts into practical algorithms. Jan 08,  · Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. Here I can suggest you the Best Machine learning Books. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 1st Edition by Aurélien Géron.