NDLI: Data Science: Understanding Computing Systems and Analytics for Big Data

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Data Science: Understanding Computing Systems and Analytics for Big Data

Content Provider	Scilit
Author	Oyana, Tonny J.
Copyright Year	2020
Description	This chapter provides practical skills and knowledge on the topic of data science, sometimes simply referred to as big data analytics, which is a recent concept that has evolved with the concurrent growth of large-scale datasets and emerging technologies to handle the volume and variety of information from multiple sources and formats. Data science draws heavily from several existing disciplines that we have discussed in this book: mathematics, statistics, computer science, geographic information system (GIS), visualization, and more, including engineering, physics, psychology, cognitive science, operations research, business, and artificial intelligence (AI). Upon the incorporation of spatial perspectives into data science, we can derive deep insights/actionable knowledge and specific information that is location-based and valuable to address simple or complex societal problems. The use and expansion of concepts, tools, and learning models derived from AI, machine learning, and deep learning, which have recently gained prominence, are given special attention in this chapter. Learners will be able to apply these new concepts, knowledge, and tools to their algorithmic spatial frameworks or analytical spatial strategies. Book Name: Spatial Analysis with R
Related Links	https://content.taylorfrancis.com/books/download?dac=C2019-0-09651-X&isbn=9781003021643&doi=10.1201/9781003021643-9&format=pdf
Ending Page	324
Page Count	28
Starting Page	297
DOI	10.1201/9781003021643-9
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-08-31
Access Restriction	Open
Subject Keyword	Book Name: Spatial Analysis with R Computation Theory and Mathematics Geographic Information System Big Data Analytics Data Science
Content Type	Text
Resource Type	Chapter

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