Principles Deep Learning Theory by Roberts Daniel (24 results)
- Hardcover
Seller: Red's Corner LLC, Tucker, GA, U.S.A.Red's Corner LLC
Contact seller5-star sellerCondition: New
US$ 74.47
US$ 4.00 shippingShips within U.S.A.Quantity: 1 available
Hardcover. Condition: New. This is a new book. All orders ship by next business day! We are a small company and very thankful for your business.
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: New
US$ 105.35
US$ 2.64 shippingShips within U.S.A.Quantity: Over 20 available
Condition: New.
- Hardcover
Seller: California Books, Miami, FL, U.S.A.California Books
Contact seller4-star sellerCondition: New
US$ 108.00
Free ShippingShips within U.S.A.Quantity: Over 20 available
Condition: New.
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: Used - As new
US$ 105.61
US$ 2.64 shippingShips within U.S.A.Quantity: Over 20 available
Condition: As New. Unread book in perfect condition.
- Hardcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
Contact seller5-star sellerCondition: New
US$ 94.16
US$ 21.14 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
hardcover. Condition: New.
- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
Contact seller5-star sellerCondition: New
US$ 100.21
US$ 16.35 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: New. In.
- Hardcover
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contact seller5-star sellerCondition: New
US$ 113.52
Free ShippingShips within U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make r…esults from the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning. This is the first book focused entirely on deep learning theory. Tools from theoretical physics are borrowed and adapted to explain, from first principles, how realistic deep neural networks work, benefiting practitioners looking to build better AI models and theorists looking for a unifying framework for understanding intelligence. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Hardcover
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.
Contact seller5-star sellerCondition: New
US$ 106.96
US$ 11.09 shippingShips from Ireland to U.S.A.Quantity: 2 available
Condition: New. 2022. New. Hardcover. . . . . .
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: New
US$ 97.64
US$ 20.47 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: New.
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: Used - As new
US$ 109.77
US$ 20.47 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: As New. Unread book in perfect condition.
- Hardcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
Contact seller5-star sellerCondition: New
US$ 130.66
Free ShippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Hardback. Condition: New. This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from…the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
US$ 116.34
US$ 20.47 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Hardcover. Condition: Brand New. 390 pages. 10.00x7.00x1.00 inches. In Stock.
- Hardcover
Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
Contact seller5-star sellerCondition: New
US$ 124.40
US$ 10.50 shippingShips within U.S.A.Quantity: 2 available
Condition: New. 2022. New. Hardcover. . . . . . Books ship from the US and Ireland.
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
Contact seller4-star sellerCondition: New
US$ 135.57
US$ 3.99 shippingShips within U.S.A.Quantity: 4 available
Condition: New. pp. 472.
- Hardcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
Contact seller5-star sellerCondition: New
US$ 114.03
US$ 29.14 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Hardback. Condition: New. New copy - Usually dispatched within 3 working days.
- Hardcover
Seller: moluna, Greven, Germanymoluna
Contact seller5-star sellerCondition: New
US$ 106.83
US$ 57.19 shippingShips from Germany to U.S.A.Quantity: 2 available
Gebunden. Condition: New. This is the first book focused entirely on deep learning theory. Tools from theoretical physics are borrowed and adapted to explain, from first principles, how realistic deep neural networks work, benefiting practitioners looking to build better AI models a.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
US$ 144.83
US$ 20.47 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Hardcover. Condition: Brand New. 390 pages. 10.00x7.00x1.00 inches. In Stock.
- Hardcover
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contact seller5-star sellerCondition: New
US$ 179.64
US$ 37.00 shippingShips from Australia to U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make r…esults from the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning. This is the first book focused entirely on deep learning theory. Tools from theoretical physics are borrowed and adapted to explain, from first principles, how realistic deep neural networks work, benefiting practitioners looking to build better AI models and theorists looking for a unifying framework for understanding intelligence. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Hardcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
Contact seller5-star sellerCondition: New
US$ 127.46
US$ 88.70 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Hardback. Condition: New. This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from…the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning.
- Hardcover
- Print on Demand
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
Contact seller5-star sellerCondition: New
US$ 106.93
US$ 29.14 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Hardcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
Contact seller4-star sellerCondition: New
US$ 135.69
US$ 8.87 shippingShips from United Kingdom to U.S.A.Quantity: 4 available
Condition: New. Print on Demand pp. 472 This item is printed on demand.
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 108.91
US$ 50.49 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make r…esults from the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning. This is the first book focused entirely on deep learning theory. Tools from theoretical physics are borrowed and adapted to explain, from first principles, how realistic deep neural networks work, benefiting practitioners looking to build better AI models and theorists looking for a unifying framework for understanding intelligence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Hardcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
Contact seller4-star sellerCondition: New
US$ 150.22
US$ 11.62 shippingShips from Germany to U.S.A.Quantity: 4 available
Condition: New. PRINT ON DEMAND pp. 472.
More images- Hardcover
- Print on Demand
Seller: preigu, Osnabrück, Germanypreigu
Contact seller5-star sellerCondition: New
US$ 114.41
US$ 81.72 shippingShips from Germany to U.S.A.Quantity: 5 available
Buch. Condition: Neu. The Principles of Deep Learning Theory | Daniel A. Roberts (u. a.) | Buch | Gebunden | Englisch | 2022 | Cambridge University Press | EAN 9781316519332 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
