Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines
Data Science on AWS by Chris Fregly and Antje Barth offers a thorough guide to building end-to-end, continuous AI and machine learning pipelines. Explore AWS services for data processing, model training, and deployment to create scalable, efficient workflows. Ideal for data scientists aiming to operationalize ML in the cloud, this book provides practical strategies for real-world implementation and automation.
About This Book
Data Science on AWS provides a detailed exploration of implementing continuous AI and machine learning pipelines using Amazon Web Services. Authors Chris Fregly and Antje Barth draw on their expertise to guide readers through the essential components of end-to-end ML workflows.
The book covers the integration of various AWS services to create robust, scalable data science solutions. It emphasizes practical approaches to handling data ingestion, processing, model training, and deployment in production environments.
Readers will learn how to leverage AWS tools for automating and optimizing ML pipelines, ensuring efficiency and reliability in real-world applications. This resource is ideal for professionals seeking to advance their skills in cloud-based data science.
With a focus on continuous integration and delivery, the content addresses challenges in maintaining ML systems over time, offering insights into best practices for operationalizing AI on AWS.
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