Overview

R CLOUD DEPLOYMENT Build Scalable Pipelines, Deploy Models, and Run Production Data Science Systems on AWS, GCP, and AzureMost R users can build models. Almost none can deploy them. That's the gap and it's why most data science work never makes it into real systems. This book is built for one purpose: turning R workflows into production-ready, cloud-native systems that actually run, scale, and deliver results. No theory dumps. No academic fluff. No shallow tutorials. Instead, you'll learn how to take real R projects and transform them into fully operational data systems-from ingestion to deployment. WHAT YOU'LL BUILD INSIDE Containerized R environments using Docker Scalable pipelines running on AWS, GCP, and Azure Real-time APIs using Plumber Automated workflows with Airflow and cloud orchestration tools Distributed data processing with Spark and parallel R Serverless R functions for event-driven systems Production-grade model deployment with CI/CD Monitoring systems that detect failures before they cost you WHAT MAKES THIS BOOK DIFFERENTMost books teach R as a language. This book teaches R as a production system. You won't just write code you'll build: Systems that run without manual intervention Pipelines that don't break under real data APIs that handle real traffic Architectures that scale with demand WHO THIS IS FOR Data scientists tired of models that never get deployed R users who want to move into production and MLOps Analysts building scalable pipelines and automation systems Engineers integrating R into cloud-based workflows WHAT YOU WALK AWAY WITHBy the end of this book, you won't just understand cloud deployment-you'll have built: A complete end-to-end R system Automated pipelines running in the cloud Scalable APIs serving real predictions A deployment workflow you can reuse across projects If your R work stops at scripts, you're leaving value on the table. This book shows you how to turn it into systems that actually run in the real world.

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