Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/982
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dc.contributor.authorPattanayak, Santanu. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:24:07Z-
dc.date.available2020-05-17T08:24:07Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484230961 ;en_US
dc.identifier.isbn9781484230954 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/982-
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionen_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionPrinted edition: ; 9781484230954. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractDeploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFloweprovides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community.e What You'll Learn: Understand full stack deep learning using TensorFlow and gain a solid mathematical foundation for deep learning Deploy complex deep learning solutions in production using TensorFlow Carry out research on deep learning and perform experiments using TensorFlow. ;en_US
dc.description.statementofresponsibilityby Santanu Pattanayak.en_US
dc.description.tableofcontentsChapter 1: Mathematical Foundations -- Chapter 2: Introduction to Deep Learning Concepts and TensorFlow -- Chapter 3: Convolutional Neural Networks -- Chapter 4: Natural Language Processing Using Recursive Neural Networks -- Chapter 5: Unsupervised Learning with Restricted Boltzmann Machines and Auto Encoders -- Chapter 6: Advanced Neural Networks. ;en_US
dc.format.extentXXI, 398 p. 189 illus., 87 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484230961.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputersen_US
dc.subjectComputer Scienceen_US
dc.subjectComputing Methodologies. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectPython. ;en_US
dc.titlePro Deep Learning with TensorFlowen_US
dc.title.alternativeA Mathematical Approach to Advanced Artificial Intelligence in Python /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.dc006 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorPattanayak, Santanu. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:24:07Z-
dc.date.available2020-05-17T08:24:07Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484230961 ;en_US
dc.identifier.isbn9781484230954 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/982-
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionen_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionPrinted edition: ; 9781484230954. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractDeploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFloweprovides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community.e What You'll Learn: Understand full stack deep learning using TensorFlow and gain a solid mathematical foundation for deep learning Deploy complex deep learning solutions in production using TensorFlow Carry out research on deep learning and perform experiments using TensorFlow. ;en_US
dc.description.statementofresponsibilityby Santanu Pattanayak.en_US
dc.description.tableofcontentsChapter 1: Mathematical Foundations -- Chapter 2: Introduction to Deep Learning Concepts and TensorFlow -- Chapter 3: Convolutional Neural Networks -- Chapter 4: Natural Language Processing Using Recursive Neural Networks -- Chapter 5: Unsupervised Learning with Restricted Boltzmann Machines and Auto Encoders -- Chapter 6: Advanced Neural Networks. ;en_US
dc.format.extentXXI, 398 p. 189 illus., 87 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484230961.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputersen_US
dc.subjectComputer Scienceen_US
dc.subjectComputing Methodologies. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectPython. ;en_US
dc.titlePro Deep Learning with TensorFlowen_US
dc.title.alternativeA Mathematical Approach to Advanced Artificial Intelligence in Python /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.dc006 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484230961.pdf15.97 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPattanayak, Santanu. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:24:07Z-
dc.date.available2020-05-17T08:24:07Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484230961 ;en_US
dc.identifier.isbn9781484230954 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/982-
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionen_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionPrinted edition: ; 9781484230954. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractDeploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFloweprovides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community.e What You'll Learn: Understand full stack deep learning using TensorFlow and gain a solid mathematical foundation for deep learning Deploy complex deep learning solutions in production using TensorFlow Carry out research on deep learning and perform experiments using TensorFlow. ;en_US
dc.description.statementofresponsibilityby Santanu Pattanayak.en_US
dc.description.tableofcontentsChapter 1: Mathematical Foundations -- Chapter 2: Introduction to Deep Learning Concepts and TensorFlow -- Chapter 3: Convolutional Neural Networks -- Chapter 4: Natural Language Processing Using Recursive Neural Networks -- Chapter 5: Unsupervised Learning with Restricted Boltzmann Machines and Auto Encoders -- Chapter 6: Advanced Neural Networks. ;en_US
dc.format.extentXXI, 398 p. 189 illus., 87 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484230961.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputersen_US
dc.subjectComputer Scienceen_US
dc.subjectComputing Methodologies. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectPython. ;en_US
dc.titlePro Deep Learning with TensorFlowen_US
dc.title.alternativeA Mathematical Approach to Advanced Artificial Intelligence in Python /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.dc006 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484230961.pdf15.97 MBAdobe PDFThumbnail
Preview File