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008			210122s2021 gw a o |||| 0|eng d
020			_a9783030570774
024	7		_a10.1007/978-3-030-57077-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _erda _dES-MaUEC
050		4	_aTK5102.9 _b2021 EB
245	0	0	_aProgramming with TensorFlow : _bSolution for Edge Computing Applications _cedited by Kolla Bhanu Prakash, G. R. Kanagachidambaresan
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (X, 190 páginas)
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aEAI/Springer Innovations in Communication and Computing _x2522-8595
490	0		_aEngineering (SpringerNature-11647)
490	0		_aEngineering (R0) (SpringerNature-43712)
505	0		_aIntroduction -- Installation Guide to Tensorflow -- Hello Tensorflow Program -- Representation of Vector -- Session with Tensorflow -- Matrix elementary operation -- Variable and constant -- Simple mathematical operation -- Matrix -- Variable Concept & Implementation -- Placeholder Concept & Implementation -- Equation with Tensor -- Matplot -- Regression Model -- Neural Network -- Convolutional Neural Network -- Recurrent Neural Network -- Application of Machine Learning & Deep Learning -- Implementing Chatbots -- Working with Text and Sequences + TensorBoard visualization -- TensorFlow Autoencoders -- Advanced TensorFlow Programming -- Reinforcement Learning -- RNN & LSTM using Keras -- Deep Learning with Pytorch -- Conclusion.
520	3		_aThis practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical audience-from data scientists and engineers to students and researchers. The authors begin by working through some basic examples in TensorFlow before diving deeper into topics such as CNN, RNN, LSTM, and GNN. The book is written for those who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. The authors demonstrate TensorFlow projects on Single Board Computers (SBCs). Provides a practical end-to-end guide to TensorFlow, the leading open source software library for building and training neural networks; Pertains to a broad technical audience-from data scientists and engineers to students and researchers; Shows how to implement advanced techniques in deep learning and explore deep neural networks and layers of data abstraction.
988			_aSpringer_Engineering_2021
650		7	_2embne _9150608 _aProceso de señales
650		7	_2embne _aTelecomunicaciones _9138448
700	1		_aPrakash, Kolla Bhanu _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aKanagachidambaresan, G. R. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-57077-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b04/2021 _dz _eb _zSI