About this book
MLOps is a systematic approach to building, deploying, and monitoring machine learning solutions. It is an engineering discipline that can be applied to many industries and use cases. This book is filled with real-world examples to help you to write programs, train robust and scalable machine learning (ML) models, and build ML pipelines to train and deploy models securely in production.
You will begin by finding out how to monitor ML and system performance in production. Then, you’ll 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. Finally, you’ll use the knowledge you’ve gained to build real-world projects.
By the end of this machine learning book, you’ll have learned how to build ML pipelines, continuous integration and continuous delivery (CI/CD) pipelines, and monitoring pipelines to systematically build, deploy, and monitor ML solutions for businesses and industries.
- Publication date:
- February 2021