Data science in practice

By:

Alby, Tom

Material type: Text

TextSeries: Data Science SeriesPublication details: CRC Press Boca Raton 2024Description: xvi, 301 pISBN:

9781032505268

Subject(s):

DDC classification:

006.31 ALB

Summary: Data Science in Practice is the ideal introduction to data science. With or without math skills, here, you get the all-round view that you need for your projects. This book describes how to properly question data, in order to unearth the treasure that data can be. You will get to know the relevant analysis methods, and will be introduced to the programming language R, which is ideally suited for data analysis. Associated tools like notebooks that make data science programming easily accessible are included in this introduction. Because technology alone is not enough, this book also deals with problems in project implementation, illuminates various fields of application, and does not forget to address ethical aspects. Data Science in Practice includes many examples, notes on errors, decision-making aids, and other practical tips. This book is ideal as a complementary text for university students, and is a useful learning tool for those moving into more data-related roles. 　 Key Features: Success factors and tools for all project phases Includes application examples for various subject areas Introduces many aspects of Data Science, from requirements analysis to data acquisition and visualization (https://www.routledge.com/Data-Science-in-Practice/Alby/p/book/9781032505268?srsltid=AfmBOopXHW5V5lU6puVznrWHRDZvHvGI4EVNsuKlCGls54jDvIc-Ud-g)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	006.31 ALB (Browse shelf(Opens below))	1	Available		006364

Data Science in Practice is the ideal introduction to data science. With or without math skills, here, you get the all-round view that you need for your projects. This book describes how to properly question data, in order to unearth the treasure that data can be. You will get to know the relevant analysis methods, and will be introduced to the programming language R, which is ideally suited for data analysis. Associated tools like notebooks that make data science programming easily accessible are included in this introduction. Because technology alone is not enough, this book also deals with problems in project implementation, illuminates various fields of application, and does not forget to address ethical aspects. Data Science in Practice includes many examples, notes on errors, decision-making aids, and other practical tips. This book is ideal as a complementary text for university students, and is a useful learning tool for those moving into more data-related roles.

　

Key Features:

Success factors and tools for all project phases

Includes application examples for various subject areas
Introduces many aspects of Data Science, from requirements analysis to data acquisition and visualization

(https://www.routledge.com/Data-Science-in-Practice/Alby/p/book/9781032505268?srsltid=AfmBOopXHW5V5lU6puVznrWHRDZvHvGI4EVNsuKlCGls54jDvIc-Ud-g)

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