Data Science on AWS

Data Science on AWS is your essential guide to implementing continuous AI and machine learning pipelines using Amazon Web Services. This book covers a wide array of topics from data ingestion to deploying models with SageMaker, ensuring you have the knowledge to build scalable AI solutions. Authored by Chris Fregly and Antje Barth, this resource provides practical examples and real-world insights for data scientists and engineers.

What You'll Learn

• How to build and optimize data pipelines on AWS
• Using SageMaker for automated machine learning
• Implementing predictive maintenance with industrial AI services
• Securing and monitoring your machine learning models
• Deploying and managing BERT models with SageMaker

Who This Book Is For

This book is designed for data scientists, AI developers, and IT professionals looking to enhance their skills in AWS cloud services. It is suitable for both beginners who are new to AWS and experienced practitioners seeking to refine their skills.

What You Need to Know First

A basic understanding of data science principles and familiarity with AWS services will be beneficial before diving into this book. Knowledge of Python programming is also recommended.

Why This Book

This book stands out by focusing on practical implementations of AI solutions on AWS, offering detailed step-by-step guidance. It covers the complete lifecycle of machine learning projects, from data ingestion to model deployment.

What's Inside

With 524 pages of content, this book includes comprehensive chapters on AWS infrastructure, SageMaker, and practical AI applications. Chris Fregly and Antje Barth bring their expertise to this detailed guide, perfect for enhancing your AWS data science skills.