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

By: Flach, Peter AMaterial type: TextTextPublisher: Cambridge ; New York : Cambridge University Press, 2012Description: xvii, 396 p. : col. ill. ; 25 cmISBN: 9781107096394 (hbk.); 1107096391 (hbk.); 9781107422223 (pbk.); 1107422221 (pbk.)Subject(s): Machine learning -- Textbooks | Apprentissage automatique -- Manuels scolairesDDC classification: 006.31 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.
Abstract: '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 location Home library Collection Shelving location Call number Status Date due Barcode Item holds
Book Book Central Library (CL)
Central Library (CL)
NFIC First Floor - Artificial Intelligence/Data Mining 006.31 FLA (Browse shelf) Checked out to Muhammad Imran Malik (37405-1201900-9) 07/08/2021 SEECS013322
Total holds: 0

Includes bibliographical references (p. 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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