Software Engineering for Data Scientists

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Software Engineering for Data ScientistsAll Indian Reprints of O'Reilly are printed in GrayscaleData science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science. Examples are provided

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Improve their debugging skills using the DevTools

Buy the Paperback version of this book

"Safeguard secrets in Azure Key Vault

and then implement helpful customer exits and workflows

He also delivers public and private courses on Chaos Engineering and Resilience Engineering around the world and online for O'Reilly Media

You will learn to implement various data warehouse and ETL concepts

review of its contributions and shortcomings and moving beyond the simplistic journalistic descriptions

"As a follow-up to their popular book

You'll learn how to run applications written in different languages on the same server

Swift is a programming language you can rely on

He has worked with clients from all over the world