Da: Bahamut Media, Reading, Regno Unito
EUR 41,36
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Aggiungi al carrellopaperback. Condizione: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.
paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Condizione: New.
Lingua: Inglese
Editore: Packt Publishing 12/12/2019, 2019
ISBN 10: 178995617X ISBN 13: 9781789956177
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Advanced Deep Learning with Python. Book.
Condizione: New.
Condizione: New.
Lingua: Inglese
Editore: Packt Publishing 11/24/2023, 2023
ISBN 10: 1837638500 ISBN 13: 9781837638505
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Python Deep Learning - Third Edition: Understand how deep neural networks work and apply them to real-world tasks. Book.
Da: California Books, Miami, FL, U.S.A.
EUR 47,25
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Da: California Books, Miami, FL, U.S.A.
EUR 48,12
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paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Condizione: As New. Unread book in perfect condition.
Condizione: As New. Unread book in perfect condition.
Condizione: New.
Lingua: Inglese
Editore: Packt Publishing 1/14/2019, 2019
ISBN 10: 1789348463 ISBN 13: 9781789348460
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Python Deep Learning - Second Edition: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Ed. Book.
Condizione: New.
Da: California Books, Miami, FL, U.S.A.
EUR 57,74
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 47,59
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Aggiungi al carrelloCondizione: New. In.
EUR 45,62
Quantità: 10 disponibili
Aggiungi al carrelloPF. Condizione: New.
Lingua: Inglese
Editore: Packt Publishing Limited, GB, 2019
ISBN 10: 178995617X ISBN 13: 9781789956177
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 63,91
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Aggiungi al carrelloPaperback. Condizione: New. Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook DescriptionIn order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application.You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural networks with fewer training samples. Finally, you'll understand how to apply deep learning to autonomous vehicles.By the end of this book, you'll have mastered key deep learning concepts and the different applications of deep learning models in the real world.What you will learnCover advanced and state-of-the-art neural network architecturesUnderstand the theory and math behind neural networksTrain DNNs and apply them to modern deep learning problemsUse CNNs for object detection and image segmentationImplement generative adversarial networks (GANs) and variational autoencoders to generate new imagesSolve natural language processing (NLP) tasks, such as machine translation, using sequence-to-sequence modelsUnderstand DL techniques, such as meta-learning and graph neural networksWho this book is forThis book is for data scientists, deep learning engineers and researchers, and AI developers who want to further their knowledge of deep learning and build innovative and unique deep learning projects. Anyone looking to get to grips with advanced use cases and methodologies adopted in the deep learning domain using real-world examples will also find this book useful. Basic understanding of deep learning concepts and working knowledge of the Python programming language is assumed.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 49,95
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Aggiungi al carrelloCondizione: New. In.
Condizione: As New. Unread book in perfect condition.
EUR 47,58
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Aggiungi al carrelloCondizione: New.
Condizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 49,94
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Aggiungi al carrelloCondizione: New.
Editore: Izdatelstvo TsK VLKSM Molodaya Gvardiya, 1981
Da: ISIA Media Verlag UG | Bukinist, Leipzig, Germania
EUR 5,50
Quantità: 1 disponibili
Aggiungi al carrelloSoftcover/Paperback. Condizione: Fair. Ivan Vasilev. KrushenieAvtor: Ivan Mikhajlovich Vasilev. Izdatelstvo: Molodaya gvardiya, Moskva. God izdaniya: 1961. Format: standartnyj. Yazyk: russkij. Strana izdaniya: SSSR. Pereplet: myagkij izdatelskij.Povest 'Krushenie' Ivana Vasileva nosit avtobiograficheskij kharakter. Avtor, prozhivshij korotkuyu, no yarkuyu zhizn 1902Nr.1938, otrazil v proizvedenii dramaticheskie sobytiya svoej epokhi. Kniga sochetaet realisticheskoe povestvovanie s glubokim sotsialnym podtekstom i otlichaetsya khudozhestvennoj tselnostyu i vospitatelnym znacheniem. Nesmotrya na to chto napisana ona v 1920-e gody, povest ne utratila svoej aktualnosti i chitabelnosti, ostavayas zhivym svidetelstvom vremeni.Sostoyanie: ekzemplyar khorosho sokhranilsya dlya svoego vozrasta. Oblozhka chistaya, s neznachitelnymi potertostyami po krayam, bez krupnykh defektov. Stranitsy pozhelteli ot vremeni, no bumaga krepkaya, tekst chitaetsya yasno. Vnutrennij blok tselyj, vladelcheskikh pometok i shtampov net.
EUR 53,38
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 58,22
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Aggiungi al carrelloCondizione: New. In.
Lingua: Inglese
Editore: Packt Publishing 2019-01-16, 2019
ISBN 10: 1789348463 ISBN 13: 9781789348460
Da: Chiron Media, Wallingford, Regno Unito
EUR 56,65
Quantità: 10 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 55,98
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Packt Publishing Limited, GB, 2019
ISBN 10: 1789348463 ISBN 13: 9781789348460
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 75,04
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Aggiungi al carrelloPaperback. Condizione: New. 2nd Revised edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python librariesKey FeaturesBuild a strong foundation in neural networks and deep learning with Python librariesExplore advanced deep learning techniques and their applications across computer vision and NLPLearn how a computer can navigate in complex environments with reinforcement learningBook DescriptionWith the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects.This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota.By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications.What you will learnGrasp the mathematical theory behind neural networks and deep learning processesInvestigate and resolve computer vision challenges using convolutional networks and capsule networksSolve generative tasks using variational autoencoders and Generative Adversarial NetworksImplement complex NLP tasks using recurrent networks (LSTM and GRU) and attention modelsExplore reinforcement learning and understand how agents behave in a complex environmentGet up to date with applications of deep learning in autonomous vehiclesWho this book is forThis book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understanding of calculus and statistics will help you gain maximum benefit from this book.