Practical MLOps: Operationalizing Machine Learning Models baixar o livro de graça

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

Procurando Practical MLOps: Operationalizing Machine Learning Models? Aqui você encontra tudo sobre este livro de Noah Gift, publicado por O'Reilly Media. Nesta página estão a descrição da obra, os detalhes da edição (458 páginas) e os formatos disponíveis para baixar: pdf, mp3, áudio-livro, kindle. Se você gosta de Livros Internacionais, Computação, Informática e Mídias Digitais, Sistemas Operacionais, Gestão de Sistemas, explore também outros títulos da mesma categoria no LivrosQualidade. Veja ainda as outras obras de Noah Gift em nosso catálogo.