Machine learning : the art and science of algorithms that make sense of data - Flach, Peter A. (Cambridge ; New York : Cambridge University Press, 2012)
'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.
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.
Includes bibliographical references (p. 367-381) and index.
Keywords: Machine learning -- Textbooks; Apprentissage automatique -- Manuels scolaires