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Condition: New.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Deep Learning : A Practical Introduction
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Deep Learning (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 2024
ISBN 10: 1119861861 ISBN 13: 9781119861867
Hardcover. Condition: new. Hardcover. An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find: Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general. "Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network."-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Deep Learning: A Practical Introduction
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Deep Learning : A Practical Introduction
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Deep Learning: A Practical Introduction
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Deep Learning
Language: English
Published by John Wiley and Sons Inc, US, 2024
ISBN 10: 1119861861 ISBN 13: 9781119861867
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find: Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general.
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Condition: New. 2024. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
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Deep Learning (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 2024
ISBN 10: 1119861861 ISBN 13: 9781119861867
US$ 107.30
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Add to basketHardcover. Condition: new. Hardcover. An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find: Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general. "Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network."-- Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Deep Learning (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 2024
ISBN 10: 1119861861 ISBN 13: 9781119861867
Hardcover. Condition: new. Hardcover. An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find: Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general. "Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network."-- Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Deep Learning
Language: English
Published by John Wiley and Sons Inc, US, 2024
ISBN 10: 1119861861 ISBN 13: 9781119861867
US$ 131.02
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Add to basketHardback. Condition: New. An engaging and accessible introduction to deep learning perfect for students and professionals In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples. Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find: Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general.
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Diagnosing Musculoskeletal Conditions Using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Diagnosing Musculoskeletal Conditions using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging (Advanced Topics in Biomaterials)
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Diagnosing Musculoskeletal Conditions Using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging
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Diagnosing Musculoskeletal Conditions using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging
Language: English
Published by Elsevier Science Publishing Co Inc Nov 2024, 2024
ISBN 10: 0443328927 ISBN 13: 9780443328923
Taschenbuch. Condition: Neu. Neuware - Bone deformations can lead to musculoskeletal disorders and negatively impact on individual quality of life. Early and accurate detection of bone deformation is crucial for effective medical intervention. Diagnosing Musculoskeletal Conditions Using Artificial Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging outlines a comprehensive approach that integrates Artificial Intelligence (AI) and Machine Learning (ML) techniques to identify bone deformations promptly and accurately. By leveraging advanced image analysis and pattern recognition, this approach aims to revolutionize the field of orthopedic diagnostics. This book covers challenges, technologies, applications, and future trends of AI and ML in Bone Deformation, addressing advanced and innovative techniques, frameworks, methodologies, and practical implementations of machine learning to get early predictions of Bone deformation. Written by experts in the field for researchers, surgeons, students, and instructors interested in musculoskeletal conditions.
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Deep Learning A Practical Introduction
Language: English
Published by John Wiley & Sons Inc, 2024
ISBN 10: 1119861861 ISBN 13: 9781119861867
US$ 122.78
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Add to basketHardcover. Condition: Brand New. 392 pages. 10.00x7.25x1.00 inches. In Stock. This item is printed on demand.
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Condition: new. Questo è un articolo print on demand.
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Add to basketPaperback. Condition: Brand New. 300 pages. 9.25x7.50x9.25 inches. In Stock. This item is printed on demand.
