Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Author: Faisal Masood and Ross Brigoli
Publisher finelybook 出版社: Packt Publishing (June 24, 2022)
Language 语言: English
Print Length 页数: 384 pages
ISBN-10: 1803241802
ISBN-13: 9781803241807
Book Description
Build a Kubernetes-based self-serving, agile data science and machine learning ecosystem for your organization using reliable and secure open source technologies
Key Features
Build a complete machine learning platform on Kubernetes
Improve the agility and velocity of your team Author: adopting the self-service capabilities of the platform
Reduce time-to-market Author: automating data pipelines and model training and deployment
MLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. Author: implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization.
You’ll begin Author: understanding the different components of a machine learning project. Then, you’ll design and build a practical end-to-end machine learning project using open source software. As you progress, you’ll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get hands-on experience in Kubernetes and open source tools, such as JupyterHub, MLflow, and Airflow.
Author: the end of this book, you’ll have learned how to effectively build, train, and deploy a machine learning model using the machine learning platform you built.
What you will learn
Understand the different stages of a machine learning project
Use open source software to build a machine learning platform on Kubernetes
Implement a complete ML project using the machine learning platform presented in this book
Improve on your organization’s collaborative journey toward machine learning
Discover how to use the platform as a data engineer, ML engineer, or data scientist
Find out how to apply machine learning to solve real business problems
