Pyzer Knapp Edward (16 results)
- Hardcover
Seller: Brook Bookstore On Demand, Napoli, ItalyBrook Bookstore On Demand
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- Hardcover
Seller: GreatBookPrices, Columbia, U.S.A.GreatBookPrices
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- Hardcover
Seller: PBShop.store UK, Fairford, United KingdomPBShop.store UK
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- Hardcover
Seller: GreatBookPrices, Columbia, U.S.A.GreatBookPrices
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Hardcover
- First Edition
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, IrelandKennys Bookshop and Art Galleries Ltd.
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Condition: New. 2021. 1st Edition. Hardcover. . . . . .
- Hardcover
Seller: Books Puddle, New York, U.S.A.Books Puddle
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: Kennys Bookstore, Olney, U.S.A.Kennys Bookstore
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Condition: New. 2021. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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£ 96.84
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Hardcover. Condition: Brand New. 248 pages. 9.60x6.69x0.83 inches. In Stock.
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 98.52
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Buch. Condition: Neu. Neuware - Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the fieldDeep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep learni…ng within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome.Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems. Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader.From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy:\* A thorough introduction to the basic classification and regression with perceptrons\* An exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of training\* An examination of multi-layer perceptrons for learning from descriptors and de-noising data\* Discussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from images\* A treatment of Bayesian optimization for tuning deep learning architecturesPerfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. This book introduces the reader to the transformative techniques involved in deep learning. A range of methodologies are addressed including: \*Basic classification and regression with perceptrons \*Training algorithms, such as back propagation and stochastic gradient descent and the parallelization of training \*Multi-Layer Perceptrons for learning from descriptors, and de-noising data \*Recurrent neural networks for learning from sequences \*Convolutional neural networks for learning from images \*Bayesian optimization for tuning deep learning architectures Each of these areas has direct application to physical science research, and by the end of the book, the reader should feel comfortable enough to select the methodology which is best for their situation, and be able to implement and interpret outcome of the deep learning model. The book is designed to teach researchers to think in new ways, providing them with new avenues to attack problems, and avoid roadblocks within their research. This is achieved through the inclusion of case-study like problems at the end of each chapter, which will give the reader a chance to practice what they have just learnt in a close-to-real-world setting, with example 'solutions' provided through an online resource. Market Description This book introduces the reader to the transformative techniques involved in deep learning. A range of methodologies are addressed including: \* Basic classification and regression with perceptrons \* Training algorithms, such as back propagation and stochastic gradient descent and the parallelization of training \* Multi-Layer Perceptrons for learning from desc.
- Hardcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, U.S.A.Grand Eagle Retail
Contact seller5-star sellerCondition: New
£ 81.24
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Hardcover. Condition: new. Hardcover. Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the field Deep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep… learning within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome. Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems. Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader. From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy: A thorough introduction to the basic classification and regression with perceptronsAn exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of trainingAn examination of multi-layer perceptrons for learning from descriptors and de-noising dataDiscussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from imagesA treatment of Bayesian optimization for tuning deep learning architectures Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Hardcover
- Print on Demand
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
£ 80.96
£ 10.00 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Hardcover. Condition: Brand New. 248 pages. 9.60x6.69x0.83 inches. In Stock. This item is printed on demand.
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
£ 73.99
£ 37.00 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the field Deep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep… learning within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome. Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems. Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader. From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy: A thorough introduction to the basic classification and regression with perceptronsAn exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of trainingAn examination of multi-layer perceptrons for learning from descriptors and de-noising dataDiscussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from imagesA treatment of Bayesian optimization for tuning deep learning architectures Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
