000			01183nam a22001697a 4500
005			20250603144953.0
008			250603b |||||||| |||| 00| 0 eng d
020			_a9781259096952
082			_a006.31 _bMIT
100			_aMitchell, Tom M
245			_aMachine learning _cMitchell, Tom M
260			_a Chennai : _bMcGraw Hill Education India Pvt. Ltd, _c 2013.
300			_axvii, 414p
505			_tChapter 1. Introduction Chapter 2. Concept Learning and the General-to-Specific Ordering Chapter 3. Decision Tree Learning Chapter 4. Artificial Neural Networks Chapter 5. Evaluating Hypotheses Chapter 6. Bayesian Learning Chapter 7. Computational Learning Theory Chapter 8. Instance-Based Learning Chapter 9. Inductive Logic Programming Chapter 10. Analytical Learning Chapter 11. Combining Inductive and Analytical Learning Chapter 12. Reinforcement Learning.
520			_a Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data. Tags from this library: No tags from this library for this title
942			_2ddc _cBK
999			_c2556 _d2556