Treveil Mark (32 results)
- Softcover
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
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- Softcover
Seller: HPB-Red, Dallas, TX, U.S.A.HPB-Red
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paperback. Condition: 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.
- Hardcover
Seller: Books From California, Simi Valley, CA, U.S.A.Books From California
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Hardcover. Condition: Good. Back hinge of spine has a small tear. Cover/edges have minor denting/scuffing.
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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- Softcover
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
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Paperback. Condition: New. More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provi…de business impact.This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout.This book helps you:Fulfill data science value by reducing friction throughout ML pipelines and workflowsRefine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracyDesign the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainableOperationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized.
- Softcover
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
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Paperback or Softback. Condition: New. Introducing Mlops: How to Scale Machine Learning in the Enterprise. Book.
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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Introducing MLOps: How to Scale Machine Learning in the Enterprise
Treveil, Mark; Omont, Nicolas; Stenac, Clément; Lefevre, Kenji; Phan, Du; Zentici, Joachim; Lavoillotte, Adrien; Miyazaki, Makoto; Heidmann, Lynn
- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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US$ 55.00
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- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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US$ 59.44
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Paperback. Condition: New. More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provi…de business impact.This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout.This book helps you:Fulfill data science value by reducing friction throughout ML pipelines and workflowsRefine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracyDesign the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainableOperationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized.
- Softcover
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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US$ 50.04
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Condition: New.
Introducing MLOps: How to Scale Machine Learning in the Enterprise
Treveil, Mark; Omont, Nicolas; Stenac, Clément; Lefevre, Kenji; Phan, Du; Zentici, Joachim; Lavoillotte, Adrien; Miyazaki, Makoto; Heidmann, Lynn
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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US$ 58.56
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Condition: New. In.
- Softcover
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.
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US$ 63.79
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Condition: New. 2020. Paperback. . . . . .
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: Used - As new
US$ 58.85
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Condition: As New. Unread book in perfect condition.
Introducing Mlops: How to Scale Machine Learning in the Enterprise
Stenac, Clement/ Dreyfus-schmidt, Leo/ Lefevre, Kenji/ Omont, Nicolas/ Treveil, Mark
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
US$ 72.71
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Paperback. Condition: Brand New. 150 pages. 9.50x7.25x0.50 inches. In Stock.
- Softcover
Seller: medimops, Berlin, Germanymedimops
Contact seller5-star sellerCondition: Used - As new
US$ 24.76
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Condition: as new. Wie neu/Like new.
- Softcover
Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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US$ 75.26
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Condition: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
Introducing MLOps: How to Scale Machine Learning in the Enterprise
Treveil, Mark; Omont, Nicolas; Stenac, Clément; Lefevre, Kenji; Phan, Du; Zentici, Joachim; Lavoillotte, Adrien; Miyazaki, Makoto; Heidmann, Lynn
- Softcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
Contact seller4-star sellerCondition: New
US$ 79.12
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Condition: New.
Introducing MLOps: How to Scale Machine Learning in the Enterprise
Treveil, Mark; Omont, Nicolas; Stenac, Clément; Lefevre, Kenji; Phan, Du; Zentici, Joachim; Lavoillotte, Adrien; Miyazaki, Makoto; Heidmann, Lynn
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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US$ 91.06
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Condition: New. 1st edition NO-PA16APR2015-KAP.
- Softcover
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
Contact seller5-star sellerCondition: New
US$ 52.81
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Paperback. Condition: New. More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provi…de business impact.This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout.This book helps you:Fulfill data science value by reducing friction throughout ML pipelines and workflowsRefine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracyDesign the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainableOperationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized.
Language: German
Published by Dpunkt.Verlag GmbH, Heidelberg, 2021
- Softcover
Seller: Paderbuch e.Kfm. Inh. Ralf R. Eichmann, Bad Lippspringe, NRW, GermanyPaderbuch e.Kfm. Inh. Ralf R. Eichmann
Contact seller5-star sellerCondition: Used - Very good
US$ 26.22
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Add to basketpaperback. Condition: Good. Mark Treveil und das Dataiku-Team: MLOps. Kernkonzepte im Überblick. Machine-Learning-Prozesse im Unternehmen nachhaltig automatisieren und skalieren. Deutsche Ausgabe. Eigenverlag O'Reilly, Heidelberg 2021. Broschur, foliert, Rückenschild, 201 Seiten; Besitz-/Inventarvermerke, sonst ordentlicher Zust…and (entwidmetes Bibl.-Ex.).
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
US$ 90.00
US$ 27.06 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Hardcover. Condition: Brand New. 408 pages. 11.73x8.27x1.10 inches. In Stock.
Condition: New
US$ 68.80
US$ 56.68 shippingShips from Germany to U.S.A.Quantity: 1 available
Condition: New. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time.Über den Autorrnrn.
MLOps in action: development. deployment and application of machine learning models(Chinese Edition)
[ YING ] MA KE TE LEI WEI ER ( Mark Treveil ) . [ MEI ] the . Dataiku . Team
- Softcover
Seller: liu xing, Nanjing, JS, Chinaliu xing
Contact seller5-star sellerCondition: New
US$ 114.42
US$ 18.00 shippingShips from China to U.S.A.Quantity: 1 available
paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2022-08-01 Pages: 159 Publisher: Machinery Industry Press This book is divided into three parts. Part 1 introduces the topic of MLOps. taking a deep dive into how (and why) it evolved into a discipline. who needs to be involved to successfully execute MLOps. and wh…at components are required. The second part introduces the life cycle of a machine learning model and includes chapters on model development. production preparation. production deployment. monit.
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
Contact seller5-star sellerCondition: New
US$ 56.59
US$ 87.93 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Paperback. Condition: New. More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provi…de business impact.This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout.This book helps you:Fulfill data science value by reducing friction throughout ML pipelines and workflowsRefine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracyDesign the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainableOperationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized.
- Hardcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
Contact seller4-star sellerCondition: New
US$ 256.38
US$ 33.82 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
- Softcover
Seller: moluna, Greven, Germanymoluna
Contact seller5-star sellerCondition: New
US$ 41.59
US$ 56.68 shippingShips from Germany to U.S.A.Quantity: 1 available
Condition: New. AUTOR: Treveil, MarkMark Treveil hat bereits zahlreiche Produkte in verschiedenen Bereichen wie etwa Telekommunikation, Bankwesen und dem Online-Boersengeschaeft konzipiert. Sein eigenes Startup hat eine regelrechte Wende in der britischen Kommunalve.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 41.59
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Taschenbuch. Condition: Neu. Neuware - Erfolgreiche ML-Pipelines entwickeln und mit MLOps organisatorische Herausforderungen meistern Stellt DevOps-Konzepte vor, die die speziellen Anforderungen von ML-Anwendungen berücksichtigen Umfasst die Verwaltung, Bereitstellung, Skalierung und Überwachung von Machine-Learning-Modellen im…Unternehmensumfeld Für Data Scientists und Data Engineers, die nach besseren Strategien für den produktiven Einsatz ihrer ML-Modelle suchen Machine-Learning-Modelle zu entwickeln ist das eine, sie im Produktivbetrieb effizient einzusetzen, eine ebenfalls nicht zu unterschätzende Herausforderung - so die Erfahrung vieler Unternehmen. Dieses Buch zeigt Ihnen, wie Sie mithilfe durchdachter MLOps-Strategien eine stabile DevOps-Umgebung für Ihre ML-Anwendungen aufbauen, Ihre Modelle kontinuierlich verbessern und langfristig warten. Das Buch erläutert MLOps-Schlüsselkonzepte, mit denen Data Scientists und Data Engineers ML-Pipelines und -Workflows optimieren können. Anhand von Fallbeispielen aus der ganzen Welt geben neun ML-Experten praxiserprobte Hilfestellungen zu den fünf Schritten des Modelllebenszyklus - Entwicklung, Preproduction, Deployment, Monitoring und Governance. Sie erfahren auf diese Weise, wie robuste MLOps-Prozesse umfassend in den ML-Produktworkflow integriert werden können. Erschließen Sie den Wert Ihrer Data-Science-Anwendungen für Ihr Unternehmen vollständig, indem Sie Störfaktoren in ML-Pipelines und -Workflows ausräumen Verfeinern Sie Ihre ML-Modelle durch Retraining, regelmäßiges Tuning und grundlegende Überarbeitung, um eine dauerhaft hohe Qualität zu gewährleisten Organisieren Sie den MLOps-Lebenszyklus so, dass Risiken, die in den Modellen stecken könnten, minimiert werden, damit die Ergebnisse unverzerrt, ausgewogen und nachvollziehbar sind Optimieren Sie ML-Modelle nicht nur für die eigene Deployment-Pipeline, sondern auch für externe Partner, deren Systeme komplexer und weniger standardisiert sind »Wenn Sie auf der Suche nach Strategien sind, um die konkreten Prozesse der ML-Entwicklung zwischen den Teams zu verbessern, ist dieses Buch genau das Richtige für Sie.« - Adi Polak, Senior Software Engineer, Microsoft.
