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(Ebook) Software Engineering for Data Scientists (MEAP V2) by Andrew Treadway ISBN 9781633438842, 1633438848

  • SKU: EBN-48497044
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Instant download (eBook) Software Engineering for Data Scientists (MEAP V2) after payment.
Authors:Andrew Treadway
Pages:213 pages.
Year:2023
Editon:chapters 1 to 7 of 14
Publisher:Manning Publications
Language:english
File Size:12.17 MB
Format:pdf
ISBNS:9781633438842, 1633438848
Categories: Ebooks

Product desciption

(Ebook) Software Engineering for Data Scientists (MEAP V2) by Andrew Treadway ISBN 9781633438842, 1633438848

These easy to learn and apply software engineering techniques will radically improve collaboration, scaling, and deployment in your data science projects.In Software Engineering for Data Scientists you’ll learn to improve performance and efficiency byUsing source controlHandling exceptions and errors in your codeImproving the design of your tools and applicationsScaling code to handle large data efficientlyTesting model and data processing code before deploymentScheduling a model to run automaticallyPackaging Python code into reusable librariesGenerating automated reports for monitoring a model in productionSoftware Engineering for Data Scientists presents important software engineering principles that will radically improve the performance and efficiency of data science projects. Author and Meta data scientist Andrew Treadway has spent over a decade guiding models and pipelines to production. This practical handbook is full of his sage advice that will change the way you structure your code, monitor model performance, and work effectively with the software engineering teams.about the technologyMany basic software engineering skills apply directly to data science! As a data scientist, learning the right software engineering techniques can save you a world of time and frustration. Source control simplifies sharing, tracking, and backing up code. Testing helps reduce future errors in your models or pipelines. Exception handling automatically responds to unexpected events as they crop up. Using established engineering conventions makes it easy to collaborate with software developers. This book teaches you to handle these situations and more in your data science projects.
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