000			01918cam a2200277 i 4500
999			_c10553 _d10553
005			20200210162852.0
008			200210s2017 cauad gr 001 0 eng d
020			_a9781491962299
040			_aUISEK-EC _bspa _erda
100	1		_aGéron, Aurélien _95316 _eaut
245	1	0	_aHands-on machine learning with Scikit-Learn and TensorFlow _bconcepts, tools, and techniques to build intelligent systems _cAurélien Géron
264	1		_aCalifornia : _bO'Reilly, _c2017
300			_axx, 549 páginas : _bilustraciones, gráficos ; _c24 cm
336			_atxt
337			_2rdamedia _an
338			_2rdacarrier _anc
505	2		_aThe fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction -- Neural networks and deep learning. Up and running with TensorFlow ; Introduction to artificial neural networks ; Training deep neural nets ; Distributing TensorFlow across devices and servers ; Convolutional neural networks ; Recurrent neural networks ; Autoencoders ; Reinforcement learning -- Exercise solutions -- Machine learning project checklist -- SVM dual problem -- Autodiff -- Other popular ANN architectures.
520			_aThrough a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
526			_aM. Tecnología de la información
546			_aTexto en inglés
082	0	4	_a006.3 _bG876h 2017
650	1	7	_aInteligencia artificial _9354 _2lemb
650	2	7	_aAprendizaje automático _95318 _2lemb
650	2	7	_aSistemas de control inteligente _95319 _2lemb
942			_cBK