Yaron Haviv, Noah Gift

Implementing MLOps in the Enterprise (eBook, PDF)

• Format: PDF

Produktbeschreibung

With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production.Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs.You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you:Learn the MLOps process, including its technological and business valueBuild and structure effective MLOps pipelinesEfficiently scale MLOps across your organizationExplore common MLOps use casesBuild MLOps pipelines for hybrid deployments, real-time predictions, and composite AILearn how to prepare for and adapt to the future of MLOpsEffectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy

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Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 380
• Erscheinungstermin: 30. November 2023
• Englisch
• ISBN-13: 9781098136550
• Artikelnr.: 72389661

Autorenporträt

Yaron Haviv is a serial entrepreneur who has been applying his deep technological experience in data, cloud, AI and networking to leading startups and enterprise companies since the late 1990s. As the co-founder and CTO of Iguazio, Yaron drives the strategy for the company's data science platform and leads the shift towards real- time AI. He also initiated and built Nuclio, a leading open source serverless platform with over 4,000 Github stars and MLRun, Iguazio's open source MLOps orchestration framework.