Jordan, David S.

Applied Geospatial Data Science with Python: Leverage geospatial data analysis and modeling to find unique solutions to environmental problems

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ISBN 13:
9781803238128
author:
Jordan, David S.
format:
Paperback
publisher:
Packt Publishing
language:
English
Publication Year:
2023
Pages:
308
Dimensions:
23.5 x 19.1 x 1.7 centimetres (0
Genre:
Computers, Computer Science, General,
Condition:
New
Availability:
Item usually sent within 5 working days
£53.43

Description

Learn to connect data points and tackle environmental problems with geospatial data science using Python. This book presents hands-on case studies that illustrate how to integrate spatial data and thinking into traditional data science workflows.

Through practical examples and code samples, you'll gain expertise in developing end-to-end spatial data science workflows, including visualization, clustering, regression, and optimization. By the end of the book, you'll be able to analyze random data, find meaningful correlations, and build geospatial models.

This book is ideal for data scientists and GIS professionals looking to learn and implement geospatial data science workflows using Python. With its focus on practical applications and real-world use cases, it's a valuable resource for anyone working in industries that rely on spatial data analysis.

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