Название: Data Science in Production: Building Scalable Model Pipelines with Python
Автор: Ben Weber
Издательство: Amazon.com Services LLC
Год: 2020
Формат: PDF, EPUB
Страниц: 234
Размер: 10 Mb
Язык: English

Putting predictive models into production is one of the most direct ways that data scientists can add value to an organization. By learning how to build and deploy scalable model pipelines, data scientists can own more of the model production process and more rapidly deliver data products.

This book provides a hands-on approach to scaling up Python code to work in distributed environments in order to build robust pipelines. Readers will learn how to set up machine learning models as web endpoints, serverless functions, and streaming pipelines using multiple cloud environments. It is intended for analytics practitioners with hands-on experience with Python libraries such as Pandas and scikit-learn, and will focus on scaling up prototype models to production.







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