Screen LibraryData science in practice /
This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often rema...
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| Group Author: | ; |
|---|---|
| Published: |
Springer,
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| Publisher Address: | Cham, Switzerland : |
| Publication Dates: | [2019] |
| Literature type: | Book |
| Language: | English |
| Series: |
Studies in big data,
volume 46 |
| Subjects: | |
| Summary: |
This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage. |
| Carrier Form: | viii, 195 pages : illustrations (some color) ; 25 cm. |
| Bibliography: | Includes bibliographical references and author index. |
| ISBN: |
9783319975559 3319975552 |
| Index Number: | QA76 |
| CLC: |
TP181 TP311.13 |
| Call Number: | TP311.13/D232-36 |