Description
Book SynopsisEffective 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.
Trade Review"Do not miss the opportunity to cover all key aspects of data science infrastructure on your next project." Jesús A. Juárez 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
