Isbn: 9780262537551 - deep learning (68 risultati)

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  • Lingua: Inglese

    Editore: MIT Press Ltd, 2019

    0262537559 / 9780262537551

    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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    Paperback. Condizione: Good. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges.…

  • Lingua: Inglese

    Editore: The MIT Press, 2019

    0262537559 / 9780262537551

    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press, 2019

    0262537559 / 9780262537551

    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press, 2019

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  • Lingua: Inglese

    Editore: MIT Press, 2019

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  • Lingua: Inglese

    Editore: The MIT Press, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press Ltd, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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    Paperback. Condizione: Good. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges.…

  • Lingua: Inglese

    Editore: The MIT Press, 2019

    0262537559 / 9780262537551

    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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    Condizione: very_good. Item may have minor cosmetic defects marks, wears, cuts, bends, crushes on the cover, spine, pages or dust cover. Shrink wrap, dust covers, or boxed set case may be missing. Item may contain remainder marks on outside edges, which should be noted in Product Details. Item may be missing bundled media.…

  • Lingua: Inglese

    Editore: MIT Press, 2019

    0262537559 / 9780262537551

    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: MIT Press, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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  • Lingua: Inglese

    Editore: The MIT Press, 2019

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    Serie: Libro 42 di 115 - MIT Press Essential Knowledge

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    Paperback. Condizione: New. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges.…

  • Lingua: Inglese

    Editore: The MIT Press, 2019

    0262537559 / 9780262537551

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  • Lingua: Inglese

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    Paperback or Softback. Condizione: New. Deep Learning. Book.

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  • Lingua: Inglese

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    Paperback. Condizione: new. Paperback. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges.An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning-major trends, possible developments, and significant challenges. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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    paperback. Condizione: Acceptable. Please see the condition note after this for details, if this is missing please consider Acceptable to mean poor quality that could include major staining, water damage, writing, missing dustjacket, etc etc. Our books are dispatched from a Yorkshire former cotton mill. We list via barcode/ISBN so please note that the images are stock images and may not be the exact copy you receive, furthermore the details about edition and year might not be accurate as many publishers reuse the same ISBN for multiple editions and as we simply scan a barcode or enter an ISBN we do not check the validity of the edition data when listing. If you're looking for an exact edition please don't order (at least not without checking with us first, although we don't always have time to check). We aim to dispatch prompty, the service used will depend on order value and book size. We can ship to most countries, see our shipping policies. Payment is via Abe only.…

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