MLOps Engineering at Scale

• Verfasst von: Osipov, Carl [VerfasserIn]
• Titel: MLOps Engineering at Scale
• Verf.angabe: Carl Osipov
• Verlagsort: New York
• Verlag: Manning Publications Co. LLC
• Jahr: 2022
• Umfang: 1 online resource (280 p.)
• Fussnoten: Description based upon print version of record. - Includes bibliographical references and index
• ISBN: 978-1-63835-650-9
• ISBN: 1-63835-650-5
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Apprentissage automatique ; Logiciels
• Sach-SW: Electronic books
• K10plus-PPN: 1801773718
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4133993403
• Lokale URL Inst.: Zum Volltext

Abstract

MLOps Engineering at Scale teaches you how to implement efficient machine learning systems using pre-built services from AWS and other cloud vendors. This easy-to-follow book guides you step-by-step as you set up your serverless ML infrastructure, even if you've never used a cloud platform before. You'll also explore tools like PyTorch Lightning, Optuna, and MLFlow that make it easy to build pipelines and scale your deep learning models in production.