000			02514cam a22004331i 4500
003			OCoLC
005			20251013123512.0
008			230202s2023 ne a ob 001 0 eng d
020			_a9780323984690
020			_a032398469X
020			_z9780323898591
041			_aEnglish
049			_aMAIN
082	0	4	_a006.31 _223 _bGOR
100	1		_aGori, Marco,
100	1		_eauthor.
245	1	0	_aMachine learning : _ba constraint-based approach.
250			_aSecond edition /
250			_bMarco Gori, Alessandro Betti, Stefano Melacci.
260			_bCambridge Morgan Kaufmann, _c2024.
300			_axviii, 537p. : _billustrations (black and white) ;
500			_aPrevious edition: published as by Marco Gori. 2018.
500			_a<p>1. The Big Picture 2. Learning Principles 3. Linear-Threshold Machines 4. Kernel Machines 5. Deep Architectures 6. Learning from Constraints 7. Epilogue 8. Answers to selected exercises</p>
504			_aIncludes bibliographical references and index.
520			_aMachine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to deep learning, which nicely fits the constrained-based approach followed in this book. The book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, including many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.
650		0	_aMachine learning.
650		0	_aAlgorithms.
700	1		_aBetti, Alessandro,
700	1		_aMelacci, Stefano,
700	1		_aGori, Marco.
700	1		_eauthor.
700	1		_eauthor.
700	1		_tMachine learning.
776	0	8	_iPrint version: _z9780323898591.
856	4	0	_uhttps://ezproxy.lib.gla.ac.uk/login?url=https://www.sciencedirect.com/science/book/9780323898591
856	4	0	_zConnect to e-book
907			_a.b40293956
942			_2ddc _cBOOKS
999			_c45912 _d45912