國立虎尾科技大學 |

SQL for data scientists = a beginner's guide for building datasets for analysis /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	SQL for data scientists/ Renée M. P. Teate.
其他題名:	a beginner's guide for building datasets for analysis /
作者:	Teate, Renée M. P.
出版者:	Hoboken, NJ :Wiley, : c2021.,
面頁冊數:	1 online resource (1 v.)
標題:	Data sets. -
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119669388
ISBN:	9781119669388

SQL for data scientists = a beginner's guide for building datasets for analysis /
Teate, Renée M. P.

SQL for data scientistsa beginner's guide for building datasets for analysis /[electronic resource] :Renée M. P. Teate. - Hoboken, NJ :Wiley,c2021. - 1 online resource (1 v.)

SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on "how to think about constructing your dataset."

ISBN: 9781119669388

Standard No.: 10.1002/9781119669388doiSubjects--Topical Terms:

1406606
Data sets.

LC Class. No.: QA76.73.S67

Dewey Class. No.: 005.756

SQL for data scientists = a beginner's guide for building datasets for analysis /
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520 $a SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on "how to think about constructing your dataset."
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