Description: Engineering MLOps by Emmanuel Raj Get to grips with ML lifecycle management and MLOps implementation for your organization. This book will give you comprehensive insights into MLOps coupled with real-world examples in Azure that will teach you how to write programs, train robust and scalable ML models, and build ML pipelines to train, deploy, and monitor models securely in ... FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Get up and running with machine learning life cycle management and implement MLOps in your organizationKey FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook DescriptionEngineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.The book begins by familiarizing you with the MLOps workflow so you can start writing programs to train ML models. Then youll then move on to explore options for serializing and packaging ML models post-training to deploy them to facilitate machine learning inference, model interoperability, and end-to-end model traceability. Youll learn how to build ML pipelines, continuous integration and continuous delivery (CI/CD) pipelines, and monitor pipelines to systematically build, deploy, monitor, and govern ML solutions for businesses and industries. Finally, youll apply the knowledge youve gained to build real-world projects.By the end of this ML book, youll have a 360-degree view of MLOps and be ready to implement MLOps in your organization.What you will learnFormulate data governance strategies and pipelines for ML training and deploymentGet to grips with implementing ML pipelines, CI/CD pipelines, and ML monitoring pipelinesDesign a robust and scalable microservice and API for test and production environmentsCurate your custom CD processes for related use cases and organizationsMonitor ML models, including monitoring data drift, model drift, and application performanceBuild and maintain automated ML systemsWho this book is forThis MLOps book is for data scientists, software engineers, DevOps engineers, machine learning engineers, and business and technology leaders who want to build, deploy, and maintain ML systems in production using MLOps principles and techniques. Basic knowledge of machine learning is necessary to get started with this book. Author Biography Emmanuel Raj is a Finland-based Senior Machine Learning Engineer with 6+ years of industry experience. He is also a Machine Learning Engineer at TietoEvry and a Member of the European AI Alliance at the European Commission. He is passionate about democratizing AI and bringing research and academia to industry. He holds a Master of Engineering degree in Big Data Analytics from Arcada University of Applied Sciences. He has a keen interest in R&D in technologies such as Edge AI, Blockchain, NLP, MLOps and Robotics. He believes "the best way to learn is to teach", he is passionate about sharing and learning new technologies with others. Table of Contents Table of ContentsFundamentals of MLOps WorkflowCharacterizing your Machine learning problemCode Meets DataMachine Learning PipelinesModel evaluation and packagingKey principles for deploying your ML systemBuilding robust CI and CD pipelinesAPIs and microservice ManagementTesting and Securing Your ML SolutionEssentials of Production ReleaseKey principles for monitoring your ML systemModel Serving and MonitoringGoverning the ML system for Continual Learning Details ISBN1800562888 Author Emmanuel Raj Short Title Engineering MLOps Language English Year 2021 ISBN-10 1800562888 ISBN-13 9781800562882 Format Paperback Publisher Packt Publishing Limited Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom Pages 370 Subtitle Rapidly build, test, and manage production-ready machine learning life cycles at scale Publication Date 2021-04-19 AU Release Date 2021-04-19 NZ Release Date 2021-04-19 UK Release Date 2021-04-19 DEWEY 006.31 Audience Professional & Vocational Replaced by 9781803237329 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:131696269;
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ISBN-13: 9781800562882
Book Title: Engineering MLOps
Item Height: 93 mm
Item Width: 75 mm
Author: Emmanuel Raj
Publication Name: Engineering MLOps: Rapidly build, test, and manage production-ready machine learning life cycles at scale
Format: Paperback
Language: English
Publisher: Packt Publishing Limited
Subject: Technology, Computer Science
Publication Year: 2021
Type: Textbook
Number of Pages: 370 Pages
