SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis
Idioma: inglés
Editorial: Wiley, 2021
- Tapa blanda
- Usado
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de AmericaWorld of Books (was SecondSale)
Vendedor de IberLibro desde 20 de diciembre de 2007
Condición: Usado - Aceptable
EUR 15,41
Cantidad disponible: 1 disponible
Añadir al carritoDescripción del artículo del vendedor
Jump-start your career as a data scientist?learn to develop datasets for exploration, analysis, and machine learning 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. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. 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." Gain an understanding of relational database structure, query design, and SQL syntaxDevelop queries to construct datasets for use in applications like interactive reports and machine learning algorithmsReview strategies and approaches so you can design analytical datasetsPractice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner?s perspective, moving your data scientist career forward.…
N° de ref. del artículo CIN1119669367G
- Título
- SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis
- Autor
- Renee M P Teate
- Editorial
- Wiley
- Año de publicación
- 2021
- Estado
- Good
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 1119669367
- ISBN 13
- 9781119669364
Jump-start your career as a data scientist―learn to develop datasets for exploration, analysis, and machine learning
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.
You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.
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."
- Gain an understanding of relational database structure, query design, and SQL syntax
- Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms
- Review strategies and approaches so you can design analytical datasets
- Practice your techniques with the provided database and SQL code
In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward!
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
RENÉE M. P. TEATE is the Director of Data Science at HelioCampus, a higher ed tech startup based in the Washington, DC area. She prepares datasets with SQL, develops predictive models with Python, and designs interactive dashboards in Tableau for university decision-makers. She created the “Becoming a Data Scientist” podcast, helped build the data science learning community on Twitter, and is a sought-after speaker at industry conferences.
“Acerca de” puede pertenecer a otra edición de este título.
World of Books (was SecondSale)
Montgomery, IL, Estados Unidos de America
Vendedor de IberLibro desde 20 de diciembre de 2007
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