000 01299nam a22002057a 4500
999 _c1949
_d1949
003 OSt
005 20181126112832.0
008 181126b ||||| |||| 00| 0 eng d
020 _a978-1-25-909695-2
028 _bAllied Informatics, Jaipur
_c5606
_d13/11/2018
_q2018-19
040 _aBSDU
_bEnglish
_cBSDU
082 _a006.31
_bMIT
100 _aMitchell, Tom M
245 _aMachine Learning
260 _aChennai
_bMcGraw Hill Education (India) Pvt. Ltd
_c2018
500 _aThis book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
504 _aContents: Chapter 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.
650 _aCSE
942 _2ddc
_cBK