Free Download Build ML Pipelines with Kubeflow: A Beginner's Cloud Deployment Guide
English | December 17, 2025 | ASIN: B0G7ZWZT9F | 79 pages | Epub | 227.18 KB
Build production-grade machine learning workflows in the cloud-without getting lost in complexity. Build ML Pipelines with Kubeflow is a hands-on, beginner-friendly guide that teaches you how to design, deploy, and manage scalable machine learning pipelines using Kubeflow, Kubernetes, and major cloud platforms like Google Cloud Platform (GCP) and Amazon Web Services (AWS). Whether you're a data scientist, ML engineer, or cloud developer, this book walks you through the essential skills needed to automate machine learning workflows from development to deployment. What You'll Learn: Understand the fundamentals of Kubeflow and MLOps Set up and configure Kubeflow on Kubernetes, both locally and in the cloud Build end-to-end ML pipelines with real-world examples Automate data preprocessing, training, and deployment using Kubeflow Pipelines Deploy ML models on GCP and AWS with confidence Monitor, scale, and manage your pipelines in production environments Packed with clear explanations, practical code samples, and step-by-step instructions, this book helps you go from zero to deploying machine learning solutions using modern DevOps practices-without the steep learning curve. Who This Book Is For: Beginners and intermediate users of Kubeflow, ML, or cloud platforms Data scientists and ML engineers looking to operationalize models DevOps engineers seeking to integrate machine learning into CI/CD workflows If you're ready to bridge the gap between machine learning and cloud deployment, this is the guide you've been looking for.
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