Librería: HPB-Red, Dallas, TX, Estados Unidos de America
EUR 32,29
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Añadir al carritopaperback. Condición: 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!
Librería: Goodwill of Silicon Valley, SAN JOSE, CA, Estados Unidos de America
EUR 35,78
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Añadir al carritoCondición: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 54,42
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 54,44
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
EUR 60,54
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Añadir al carritoPaperback. Condición: New. This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.Google engineers Valliappa Lakshmanan, Martin Goerner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.You'll learn how to:Design ML architecture for computer vision tasksSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your taskCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your modelPreprocess images for data augmentation and to support learnabilityIncorporate explainability and responsible AI best practicesDeploy image models as web services or on edge devicesMonitor and manage ML models.
Librería: Mooney's bookstore, Den Helder, Holanda
EUR 52,50
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: Very good.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 56,66
Cantidad disponible: 17 disponibles
Añadir al carritoCondición: New.
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 77,21
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: New. This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.Google engineers Valliappa Lakshmanan, Martin Goerner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.You'll learn how to:Design ML architecture for computer vision tasksSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your taskCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your modelPreprocess images for data augmentation and to support learnabilityIncorporate explainability and responsible AI best practicesDeploy image models as web services or on edge devicesMonitor and manage ML models.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 65,52
Cantidad disponible: 2 disponibles
Añadir al carritoCondición: New. In.
Idioma: Inglés
Publicado por O'Reilly Media 2021-08-31, 2021
ISBN 10: 1098102363 ISBN 13: 9781098102364
Librería: Chiron Media, Wallingford, Reino Unido
EUR 62,81
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 62,34
Cantidad disponible: 17 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 93,94
Cantidad disponible: 3 disponibles
Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2021
ISBN 10: 1098102363 ISBN 13: 9781098102364
Librería: Revaluation Books, Exeter, Reino Unido
EUR 88,02
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 350 pages. 9.19x7.00x0.97 inches. In Stock.
EUR 56,67
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 62,46
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: New. This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.Google engineers Valliappa Lakshmanan, Martin Goerner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.You'll learn how to:Design ML architecture for computer vision tasksSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your taskCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your modelPreprocess images for data augmentation and to support learnabilityIncorporate explainability and responsible AI best practicesDeploy image models as web services or on edge devicesMonitor and manage ML models.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 112,20
Cantidad disponible: 3 disponibles
Añadir al carritoCondición: New.
Librería: moluna, Greven, Alemania
EUR 76,06
Cantidad disponible: 2 disponibles
Añadir al carritoCondición: New. This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image gene.
EUR 72,03
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: New. This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.Google engineers Valliappa Lakshmanan, Martin Goerner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.You'll learn how to:Design ML architecture for computer vision tasksSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your taskCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your modelPreprocess images for data augmentation and to support learnabilityIncorporate explainability and responsible AI best practicesDeploy image models as web services or on edge devicesMonitor and manage ML models.
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2021
ISBN 10: 1098102363 ISBN 13: 9781098102364
Librería: Revaluation Books, Exeter, Reino Unido
EUR 81,88
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 350 pages. 9.19x7.00x0.97 inches. In Stock. This item is printed on demand.