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Data Science in Practice: Studies in Big Data, cartea 46

Editat de Alan Said, Vicenç Torra
en Limba Engleză Hardback – 27 sep 2018
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.
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Specificații

ISBN-13: 9783319975559
ISBN-10: 3319975552
Pagini: 197
Ilustrații: VIII, 195 p. 43 illus., 15 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.46 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Big Data

Locul publicării:Cham, Switzerland

Cuprins

Artificial intelligence.- Machine learning: a concise overview.- Information fusion.- Information retrieval & recommender systems.- Business intelligence.- Data privacy.- Visual data analysis.- Complex data analysis.- Big data programming with Apache Spark.

Textul de pe ultima copertă

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. 

Caracteristici

Presents the latest research on Data Science in Practice Especially focuses on the applications of Data Science and Big Data Written by respected experts in the field