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Ultimate MLOps for Machine Learning Models Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps - Saurabh D. Dorle 2024 PDF | EPUB Orange Education Pvt Ltd, AVA BOOKS
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Ultimate MLOps for Machine Learning Models Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps
Author: Saurabh D. Dorle
Year: 2024
Format: PDF | EPUB
File size: 10.1 MB
Language: ENG



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The book "Ultimate MLOps for Machine Learning Models" by Michael A. Hugues, published by Packt Publishing, provides a comprehensive guide to implementing MLOps in machine learning pipelines. The author emphasizes the importance of understanding the technological process of developing modern knowledge as the basis for the survival of humanity and the unity of people in a warring state. The book focuses on real-world case studies to demonstrate practical applications of MLOps and its benefits in building, deploying, and scaling machine learning models. The first chapter, "Introduction to MLOps provides an overview of the field and its significance in the development of machine learning models. The author highlights the need for a systematic approach to managing the entire lifecycle of machine learning models, from inception to deployment and maintenance. This chapter also introduces the concept of the "MLOps cycle which consists of four stages: plan, build, deploy, and maintain. In the second chapter, "Planning and Designing Your MLOps Pipeline the author discusses the importance of planning and designing an MLOps pipeline before implementation. This includes identifying the goals and objectives of the project, selecting the appropriate technology stack, and defining the roles and responsibilities of team members. The author also emphasizes the need for version control and documentation throughout the development process.
Книга «Ultimate MLOps for Machine arning Models» Майкла А. Хьюга, опубликованная Packt Publishing, содержит исчерпывающее руководство по внедрению MLOps в конвейеры машинного обучения. Автор подчеркивает важность понимания технологического процесса развития современного знания как основы выживания человечества и единства людей в воюющем государстве. Книга фокусируется на реальных тематических исследованиях, чтобы продемонстрировать практическое применение MLOps и его преимущества в создании, развертывании и масштабировании моделей машинного обучения. Первая глава, "Введение в MLOps, дает обзор области и ее значения в разработке моделей машинного обучения. Автор подчеркивает необходимость системного подхода к управлению всем жизненным циклом моделей машинного обучения, от создания до развертывания и обслуживания. В этой главе также представлена концепция "цикла MLOps, который состоит из четырех этапов: планирование, создание, развертывание и поддержка. Во второй главе «Планирование и проектирование трубопровода MLOps» автор обсуждает важность планирования и проектирования трубопровода MLOps перед внедрением. Сюда входит определение целей и задач проекта, выбор соответствующего технологического стека и определение ролей и обязанностей членов группы. Автор также подчеркивает необходимость контроля версий и документации на протяжении всего процесса разработки.
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