Description: Serverless Machine Learning with Amazon Redshift ML by Phil Bates, Bhanu Pittampally, Sumeet Joshi, Debu Panda, Colin Mahony This book helps you implement end-to-end serverless architectures for ingestion, analytics, and machine learning using Redshift Serverless and Redshift ML. FORMAT Paperback CONDITION Brand New Publisher Description Supercharge and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scaleKey FeaturesLeverage supervised learning to build binary classification, multi-class classification, and regression modelsLearn to use unsupervised learning using the K-means clustering methodMaster the art of time series forecasting using Redshift MLPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAmazon 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, youll then learn to build your own classification and regression models. As you advance, youll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, youll discover best practices for implementing serverless architecture with Redshift.By the end of this book, youll 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.What you will learnUtilize Redshift Serverless for data ingestion, data analysis, and machine learningCreate supervised and unsupervised models and learn how to supply your own custom parametersDiscover how to use time series forecasting in your data warehouseCreate a SageMaker endpoint and use that to build a Redshift ML model for remote inferenceFind out how to operationalize machine learning in your data warehouseUse model explainability and calculate probabilities with Amazon Redshift MLWho this book is forData scientists and machine learning developers working with Amazon Redshift who want to explore its machine-learning capabilities will find this definitive guide helpful. A basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to make the most of this book. Author Biography 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. Table of Contents Table of ContentsIntroduction to Redshift ServerlessData Loading and Analytics on Redshift ServerlessApplying Machine Learning in Your Data Warehouse Leveraging Amazon Redshift Machine Learning Building Your First Machine Learning ModelBuilding Classification ModelsBuilding Regression ModelsBuilding Unsupervised Models with K-Means ClusteringDeep Learning with Redshift MLCreating Custom ML Models with XGBoostBring Your Own Models for in Database InferenceTime-Series Forecasting in your Data WarehouseOperationalizing and Optimizing Amazon Redshift ML Models Details ISBN1804619280 Author Colin Mahony Publisher Packt Publishing Limited Year 2023 ISBN-13 9781804619285 Format Paperback Imprint Packt Publishing Limited Subtitle Create, train, and deploy machine learning models using familiar SQL commands Place of Publication Birmingham Country of Publication United Kingdom AU Release Date 2023-04-28 NZ Release Date 2023-04-28 Pages 290 Publication Date 2023-08-30 DEWEY 006.3 Audience Professional & Vocational UK Release Date 2023-08-30 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:159627778;
Price: 107.21 AUD
Location: Melbourne
End Time: 2024-11-24T02:06:09.000Z
Shipping Cost: 23.83 AUD
Product Images
Item Specifics
Restocking fee: No
Return shipping will be paid by: Buyer
Returns Accepted: Returns Accepted
Item must be returned within: 30 Days
Format: Paperback
ISBN-13: 9781804619285
Author: Phil Bates, Bhanu Pittampally, Sumeet Joshi, Debu Panda
Type: Does not apply
Book Title: Serverless Machine Learning with Amazon Redshift ML
Language: Does not apply
