Overview

Effective Data Science Infrastructure is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data driven companies to manage their cutting edge data infrastructure. As you work through this easy-to-follow guide, you'll set up end-to end infrastructure from the ground up, with a fully customizable process you can easily adapt to your company. You'll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python. Throughout, you'll follow a human-centric approach focused on user experience and meeting the unique needs of data scientists. About the Technology Turning data science projects from small prototypes to sustainable business processes requires scalable and reliable infrastructure. This book lays out the workflows, components, and methods of the full infrastructure stack for data science, from data warehousing and scalable compute to modeling frameworks.

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9781617299193

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Reviews

Do not miss the opportunity to cover all key aspects of data science infrastructure on your next project. Jesus A. Juarez Guerrero Useful book that provides tactical guidance on how to use Metaflow to streamline data science workflows but also includes great frameworks and abstractions to consider when defining your data science infrastructure stack. Sarah Catanzaro This is the ultimate book to learn how to handle infrastructure in data science! Ninoslav Cerkez If you need a workflow management tool to glue your data code, look at metaflow. It's simple yet efficient. Mikael Dautrey

Author Information

Ville Tuulos has been developing tools and infrastructure for data science and machine learning for over two decades. At Netflix, he designed and built Metaflow, a full-stack framework for data science. Currently, he is the CEO of a startup focusing on data science infrastructure.

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