000			01845nam\a2200349\a\4500
001			57811
005			20260602155154.0
008			260602t20202020nyua 001 0 eng d
020			_qpaperback
020			_a9781617296079 _qpaperback
040			_aYDX _beng _cYDX _erda _dOCLCQ _dJBL _dOCLCF _dOCLCO _dYDXIT _dTOH _dQGQ _dBD-DhIUB
082	0	4	_a006.31 _223 _bD9651p
100	1		_aDürr, Oliver, _eauthor.
245	1	0	_aProbabilistic deep learning : _bwith Python, Keras, and TensorFlow Probability / _cOliver Dürr, Beate Sick ; with Elvis Murina.
260			_aNew York: _bManning Publications Co. _c2020
300			_axviii, 274 pages : _billustrations ; _c24 cm
500			_aIncludes index.
500			_a"Exercises in Jupyter Notebooks"--Page 1 of cover.
505	0		_aPart 1, Basics of deep learning. Introduction to probabilistic deep learning ; Neural network architectures ; Principles of curve fitting -- Part 2, Maximum likelihood approaches for probabilistic DL models. Building loss functions with the likelihood approach ; Probabilistic deep learning models with TensorFlow Probability ; Probabilistic deep learning models in the wild -- Part 3, Bayesian approaches for probabilistic DL models. Bayesian learning ; Bayesian neural networks.
520			_a"A hands-on guide to the principles that support neural networks"--
521	8		_a"For experience machine learning developers"--Page 4 of cover.
526			_aCSE _bps _lREF
541			_aOmni concept
650		0	_aMachine learning.
650		0	_aNeural networks (Computer science)
650		7	_aMachine learning. _2fast
650		7	_aNeural networks (Computer science) _2fast
700	1		_aSick, Beate, _eauthor.
700	1		_aMurina, Elvis, _eauthor.
942			_2ddc _cBK
999			_c57811 _d57985