Engineering MLOps [ebook]
Engineering MLOps
About the Book
Book description
Get up and running with machine learning life cycle management and implement MLOps in your organization
Key Features
- Become well-versed with MLOps techniques to monitor the quality of machine learning models in production
- Explore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed models
- Perform CI/CD to automate new implementations in ML pipelines
Book Description
Engineering 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 you’ll 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. You’ll 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, you’ll apply the knowledge you’ve gained to build real-world projects.
By the end of this ML book, you'll have a 360-degree view of MLOps and be ready to implement MLOps in your organization.
What you will learn
- Formulate data governance strategies and pipelines for ML training and deployment
- Get to grips with implementing ML pipelines, CI/CD pipelines, and ML monitoring pipelines
- Design a robust and scalable microservice and API for test and production environments
- Curate your custom CD processes for related use cases and organizations
- Monitor ML models, including monitoring data drift, model drift, and application performance
- Build and maintain automated ML systems
Who this book is for
This 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.
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Author Details

<a href="https://market.tutorialspoint.com/author/emmanuel_raj">Emmanuel Raj</a>
Packt are an established, trusted, and innovative global technical learning publisher, founded in Birmingham, UK with over eighteen years experience delivering rich premium content from ground-breaking authors and lecturers on a wide range of emerging and established technologies for professional development.
Packt’s purpose is to help technology professionals advance their knowledge and support the growth of new technologies by publishing vital user focused knowledge-based content faster than any other tech publisher, with a growing library of over 9,000 titles, in book, e-book, audio and video learning formats, our multimedia content is valued as a vital learning tool and offers exceptional support for the development of technology knowledge.
We publish on topics that are at the very cutting edge of technology, helping IT professionals learn about the newest tools and frameworks in a way that suits them.
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