在 Azure 上使用 T-SQL 和 Python 的 SQL 数据仓库数据科学演练SQL Data Warehouse data science walkthroughs using T-SQL and Python on Azure

这些演练使用 SQL 数据仓库进行预测分析。These walkthroughs use of SQL Data Warehouse to do predictive analytics. 它们遵循 Team Data Science Process 中所述的步骤。They follow the steps outlined in the Team Data Science Process. 有关 Team Data Science Process 的概述,请参阅数据科学过程For an overview of the Team Data Science Process, see Data Science Process. 有关 SQL 数据仓库的简介,请参阅什么是 Azure SQL 数据仓库?For an introduction to SQL Data Warehouse, see What is Azure SQL Data Warehouse?

其他执行 Team Data Science Process 的数据科学演练按所使用的平台分组。Additional data science walkthroughs that execute the Team Data Science Process are grouped by the platform that they use. 有关这些示例的明细,请参阅执行 Team Data Science Process 的演练See Walkthroughs executing the Team Data Science Process for an itemization of these examples.

在 SQL 数据仓库中使用 T-SQL 和 IPython 笔记本预测出租车小费Predict taxi tips using T-SQL and IPython notebooks with SQL Data Warehouse

“使用 SQL 数据仓库”演练展示如何使用 SQL 数据仓库 (SQL DW) 生成和部署机器学习分类模型以及回归模型。The Use SQL Data Warehouse walkthrough shows you how to build and deploy machine learning classification and regression models using SQL Data Warehouse (SQL DW). 所用数据是公开提供的纽约市出租车行程和费用数据集。The data are a publicly available NYC taxi trip and fare dataset.

后续步骤Next steps

有关构成 Team Data Science Process 的关键组件的讨论,请参阅 Team Data Science Process 概述For a discussion of the key components that comprise the Team Data Science Process, see Team Data Science Process overview.

有关 Team Data Science Process 生命周期的讨论,请参阅 Team Data Science Process 生命周期For a discussion of the Team Data Science Process lifecycle, see Team Data Science Process lifecycle. 此生命周期概述了执行项目时,其从开始到结束所遵循的步骤。This lifecycle outlines the steps, from start to finish, that projects usually follow when they are executed.