Von dem Buch Practical MLOps haben wir 2 gleiche oder sehr ähnliche Ausgaben identifiziert!
Falls Sie nur an einem bestimmten Exempar interessiert sind, können Sie aus der folgenden Liste jenes wählen, an dem Sie interessiert sind:
100%: Practical Mlops (ISBN: 9781098102968) Vitalsource Technologies, Inc., in Englisch.Nur diese Ausgabe anzeigen…
Practical MLOps - 2 Angebote vergleichen
Bester Preis: € 40,27 (vom 30.09.2021)1
Practical MLOps
EN NW EB DLISBN: 9781098102982 bzw. 1098102983, in Englisch, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigte Staaten von Amerika, In Stock, plus shipping.
Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start. You'll discover how to: Apply DevOps best practices to machine learning Build production machine learning systems and maintain them Monitor, instrument, load-test, and operationalize machine learning systems Choose the correct MLOps tools for a given machine learning task Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware.
Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start. You'll discover how to: Apply DevOps best practices to machine learning Build production machine learning systems and maintain them Monitor, instrument, load-test, and operationalize machine learning systems Choose the correct MLOps tools for a given machine learning task Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware.
Lade…