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Machine learning : the art and science of algorithms that make sense of data / Peter Flach.

By: Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2012Description: xvii, 396 pages : color illustrations ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781107422223
  • 1107422221
Subject(s): DDC classification:
  • 006.31 FA.M 2012 23
LOC classification:
  • Q325.5 .F53 2012
Contents:
1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here.
Summary: 'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.
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Item type Current library Collection Call number Status Date due Barcode
Books Books The Knowledge Hub Library Computing 006.31 FA.M 2012 (Browse shelf(Opens below)) Available 190266

Includes bibliographical references (pages 367-381) and index.

1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here.

'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.

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