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Añadir al carritoPaperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.04.
Librería: California Books, Miami, FL, Estados Unidos de America
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Packt Publishing Limited, GB, 2018
ISBN 10: 1789130336 ISBN 13: 9781789130331
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
EUR 39,74
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Añadir al carritoPaperback. Condición: New. Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges.Key FeaturesLearn the fundamentals of Convolutional Neural NetworksHarness Python and Tensorflow to train CNNsBuild scalable deep learning models that can process millions of itemsBook DescriptionConvolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation.After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks.Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images. What you will learnTrain machine learning models with TensorFlowCreate systems that can evolve and scale during their life cycleUse CNNs in image recognition and classificationUse TensorFlow for building deep learning models Train popular deep learning modelsFine-tune a neural network to improve the quality of results with transfer learningBuild TensorFlow models that can scale to large datasets and systemsWho this book is forThis book is for Software Engineers, Data Scientists, or Machine Learning practitioners who want to use CNNs for solving real-world problems. Knowledge of basic machine learning concepts, linear algebra and Python will help.
Publicado por Packt Publishing 8/29/2018, 2018
ISBN 10: 1789130336 ISBN 13: 9781789130331
Idioma: Inglés
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 33,14
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Añadir al carritoPaperback or Softback. Condición: New. Hands-on Convolutional Neural Networks with Tensorflow 1.04. Book.
Publicado por Packt Publishing Limited, GB, 2018
ISBN 10: 1789130336 ISBN 13: 9781789130331
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 45,05
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Añadir al carritoPaperback. Condición: New. Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges.Key FeaturesLearn the fundamentals of Convolutional Neural NetworksHarness Python and Tensorflow to train CNNsBuild scalable deep learning models that can process millions of itemsBook DescriptionConvolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation.After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks.Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images. What you will learnTrain machine learning models with TensorFlowCreate systems that can evolve and scale during their life cycleUse CNNs in image recognition and classificationUse TensorFlow for building deep learning models Train popular deep learning modelsFine-tune a neural network to improve the quality of results with transfer learningBuild TensorFlow models that can scale to large datasets and systemsWho this book is forThis book is for Software Engineers, Data Scientists, or Machine Learning practitioners who want to use CNNs for solving real-world problems. Knowledge of basic machine learning concepts, linear algebra and Python will help.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 30,39
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Publicado por Packt Publishing, United Kingdom, 2018
ISBN 10: 1789130336 ISBN 13: 9781789130331
Idioma: Inglés
Librería: True Oak Books, Highland, NY, Estados Unidos de America
Miembro de asociación: IOBA
Original o primera edición
EUR 26,55
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Añadir al carritoPaperback. Condición: Very Good+. First Edition. 259 pages; Graphs. B&W illustrations. Very minor smudge on title page. Very Good condition otherwise. No other noteworthy defects. No markings. ; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be carefully cushioned in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 40,20
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Añadir al carritoCondición: New. pp. 272.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 39,38
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Añadir al carritoCondición: New. Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python l.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 29,20
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Librería: SecondSale, Montgomery, IL, Estados Unidos de America
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Añadir al carritoCondición: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Publicado por Packt Publishing Limited, 2018
ISBN 10: 1789130336 ISBN 13: 9781789130331
Idioma: Inglés
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 39,67
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por Packt Publishing Limited, 2018
ISBN 10: 1789130336 ISBN 13: 9781789130331
Idioma: Inglés
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 37,94
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 520.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 39,42
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Añadir al carritoCondición: New. Print on Demand pp. 272.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 272.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.