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Serverless Machine Learning with Amazon Redshift ML. Create, train, and deploy machine learning models using familiar SQL commands

(ebook) (audiobook) (audiobook) Książka w języku 1
Serverless Machine Learning with Amazon Redshift ML. Create, train, and deploy machine learning models using familiar SQL commands Debu Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi, Colin Mahony - okladka książki

Serverless Machine Learning with Amazon Redshift ML. Create, train, and deploy machine learning models using familiar SQL commands Debu Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi, Colin Mahony - okladka książki

Serverless Machine Learning with Amazon Redshift ML. Create, train, and deploy machine learning models using familiar SQL commands Debu Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi, Colin Mahony - audiobook MP3

Serverless Machine Learning with Amazon Redshift ML. Create, train, and deploy machine learning models using familiar SQL commands Debu Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi, Colin Mahony - audiobook CD

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290
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Do przechowalni

Amazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models.
The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift.
By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.

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O autorach książki

Debu Panda, a Senior Manager, Product Management at AWS, is an industry leader in analytics, application platform, and database technologies, and has more than 25 years of experience in the IT world. Debu has published numerous articles on analytics, enterprise Java, and databases and has presented at multiple conferences such as re:Invent, Oracle Open World, and Java One. He is lead author of the EJB 3 in Action (Manning Publications 2007, 2014) and Middleware Management (Packt, 2009).
Phil Bates is a Senior Analytics Specialist Solutions Architect at AWS. He has more than 25 years of experience implementing large-scale data warehouse solutions. He is passionate about helping customers through their cloud journey and leveraging the power of ML within their data warehouse.
Bhanu Pittampally is Analytics Specialist Solutions Architect at Amazon Web Services. His background is in data and analytics and is in the field for over 16 years. He currently lives in Frisco, TX with his wife Kavitha and daughters Vibha and Medha.
Sumeet Joshi is an Analytics Specialist Solutions Architect based out of New York. He specializes in building large-scale data warehousing solutions. He has over 17 years of experience in the data warehousing and analytical space.

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