Data Science in Practice / edited by Alan Said, Vicenç Torra.
Contributor(s): SpringerLink (Online service)
| Said, Alan., editor literario | Torra, Vicenç., editor literario
Series: (Studies in Big Data, 2197-6503; 46); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Description: 1 recurso en línea (VIII, 195 páginas) : 43 ilustraciones,15 ilustraciones a color.ISBN: 9783319975566.Subject: Datos masivos
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9.B45 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBooks26062033 |
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| QA76.9 .B45 2019 EB Large Scale Data Analytics | QA76.9.B45 2019 EB Big Data Processing Using Spark in Cloud | QA76.9.B45 2019 EB Clustering Methods for Big Data Analytics : Techniques, Toolboxes and Applications | QA76.9.B45 2019 EB Data Science in Practice | QA76.9 .B45 2019 EB Data Science and Big Data Analytics : ACM-WIR 2018 | QA76.9 .B45 2019 EB Big Data-Driven World : Legislation Issues and Control Technologies | QA76.9 .B45 2019 EB Big data, cloud computing, data science & engineering |
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.
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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