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000839012 019__ $$a1035297574
000839012 020__ $$a9781484234532$$q(electronic book)
000839012 020__ $$a1484234537$$q(electronic book)
000839012 020__ $$z9781484234525
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000839012 0247_ $$a10.1007/978-1-4842-3453-2$$2doi
000839012 035__ $$aSP(OCoLC)on1034550490
000839012 035__ $$aSP(OCoLC)1034550490$$z(OCoLC)1035297574
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000839012 049__ $$aISEA
000839012 050_4 $$aQ325.5
000839012 08204 $$a006.3/1$$223
000839012 1001_ $$aVieira, Armando,$$eauthor.
000839012 24510 $$aIntroduction to deep learning business applications for developers :$$bfrom conversational bots in customer service to medical image processing /$$cArmando Vieira, Bernardete Ribeiro.
000839012 264_1 $$aBerkeley, CA :$$bApress,$$c2018.
000839012 300__ $$a1 online resource (xxi, 343 pages) :$$billustrations.
000839012 336__ $$atext$$btxt$$2rdacontent
000839012 337__ $$acomputer$$bc$$2rdamedia
000839012 338__ $$aonline resource$$bcr$$2rdacarrier
000839012 347__ $$atext file$$bPDF$$2rda
000839012 504__ $$aIncludes bibliographical references and index.
000839012 5050_ $$a1 Introduction -- 2 Deep Learning: An Overview -- 3 Deep Neural Network Models -- 4 Image Processing -- 5 Natural Language Processing and Speech -- 6 Reinforcement Learning and Robotics -- 7 Recommendations Algorithms and Advertising -- 8 Games and Art -- 9 Other Applications -- 10 Business Impact of DL Technology -- 11 New Research and Future Directions -- Appendix Training DNN with Keras.
000839012 506__ $$aAccess limited to authorized users.
000839012 520__ $$aDiscover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You'll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) that can be applied for image colorization, image completion, and style transfer. After reading this book you will have an overview of the exciting field of deep neural networks and an understanding of most of the major applications of deep learning. The book contains some coding examples, tricks, and insights on how to train deep learning models using the Keras framework. You will: Find out about deep learning and why it is so powerful Work with the major algorithms available to train deep learning models See the major breakthroughs in terms of applications of deep learning Run simple examples with a selection of deep learning libraries Discover the areas of impact of deep learning in business.
000839012 650_0 $$aMachine learning.
000839012 650_0 $$aApplication software$$xDevelopment.
000839012 650_0 $$aComputer science.
000839012 650_0 $$aComputers.
000839012 7001_ $$aRibeiro, Bernardete,$$eauthor.
000839012 77608 $$iPrint version:$$z9781484234525
000839012 852__ $$bebk
000839012 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-1-4842-3453-2$$zOnline Access$$91397441.1
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000839012 980__ $$aEBOOK
000839012 980__ $$aBIB
000839012 982__ $$aEbook
000839012 983__ $$aOnline
000839012 994__ $$a92$$bISE