Kubeflow Operations Guide: Managing Cloud and On-Premise Deployment
Focus:
The book addresses the complexities of deploying machine learning applications beyond just building models.
It emphasizes the orchestration, deployment, and running of scalable and portable machine learning workloads using Kubeflow.
Key Content:
Provides practical guidance for data scientists, data engineers, and platform architects on planning and executing Kubeflow projects.
Explains how Kubeflow simplifies Kubernetes workflows for machine learning.
Covers Kubeflow architecture and best practices.
Details the planning and execution of Kubeflow deployments across on-premises and cloud environments (Google Cloud Platform, AWS, Azure).
Explores the use of KFServing for developing and deploying machine learning models.
Overall:
The book serves as a practical guide for those seeking to implement and manage Kubeflow for efficient machine learning operations.
It helps to bridge the gap between model building and production level machine learning deployments.
By John Patterson
Paperback
Excellent Used Condition - see images
