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Applied Geospatial Data Science with Python
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ÀúÀÚ Jordan, David S.
ÃâÆÇ»ç/¹ßÇàÀÏ Packt Publishing / 2023.02.28
ÆäÀÌÁö ¼ö 308 page
ISBN 9781803238128
»óÇ°ÄÚµå 356727885
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Part 1:The Essentials of Geospatial Data Science Chapter 1: Introducing Geographic Information Systems and Geospatial Data Science Chapter 2: What Is Geospatial Data and Where Can I Find It? Chapter 3: Working with Geographic and Projected Coordinate Systems Chapter 4: Exploring Geospatial Data Science Packages Part 2: Exploratory Spatial Data Analysis Chapter 5: Exploratory Data Visualization Chapter 6: Hypothesis Testing and Spatial Randomness Chapter 7: Spatial Feature Engineering Part 3: Geospatial Modeling Case Studies Chapter 8: Spatial Clustering and Regionalization Chapter 9: Developing Spatial Regression Models Chapter 10: Developing Solutions for Spatial Optimization Problems Chapter 11: Advanced Topics in Spatial Data Science Index Other Books You May Enjoy

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Jordan, David S.
David S. Jordan has made a career out of applying spatial thinking to tough problem spaces in the domains of real estate planning, disaster response, social equity, and climate change. He currently leads distribution and geospatial data science at JPMorgan Chase & Co. In addition to leading and building out geospatial data science teams, David is a patented inventor of new geospatial analytics processes, a winner of a Special Achievement in GIS (SAG) Award from Esri, and a conference speaker on topics including banking deserts and how great businesses leverage GIS.

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