SQML: large-scale in-database machine learning with pure SQL

Umar Syed, Sergei Vassilvitskii
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引用次数: 6

Abstract

Many enterprises have migrated their data from an on-site database to a cloud-based database-as-a-service that handles all database-related administrative tasks while providing a simple SQL interface to the end user. Businesses are also increasingly relying on machine learning to understand their customers and develop new products. Given these converging trends, there is a pressing need for database-as-a-service providers to add support for sophisticated machine learning algorithms to the core functionality of their products.
SQL:使用纯SQL的大规模数据库内机器学习
许多企业已将其数据从现场数据库迁移到基于云的数据库即服务,该服务处理所有与数据库相关的管理任务,同时向最终用户提供简单的SQL接口。企业也越来越依赖机器学习来了解客户和开发新产品。鉴于这些趋同的趋势,数据库即服务提供商迫切需要在其产品的核心功能中添加对复杂机器学习算法的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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