Book Review - Applied Geospatial Data Science with Python

When faced with a vast amount of data, data scientists may struggle to present geospatial analysis in a way that is comprehensible to a wider audience. Visualizing data through Python enables individuals in non-technical roles to better grasp the issue at hand and explore solutions. This book aims to guide data scientists and GIS professionals in mastering geospatial data science workflows using Python. As you delve into the book, you will discover numerous geospatial Python libraries that enable the creation of complete spatial data science workflows. You will acquire skills to read, process, and manipulate spatial data efficiently. Armed with this data, you will then create spatial data visualizations to enhance understanding and narrate the data story via static and dynamic mapping applications. Advancing through the book, you will develop geospatial AI and ML models centered on clustering, regression, and optimization. These use cases can serve as foundations for more sophisticated projects across various industries. By the book's conclusion, you will have the ability to handle random data, identify meaningful connections, and create geospatial data models.

#Geospatial #geospatialdata

You'll learn:

✅Introduce Geographic Information Systems, Geospatial Data Science, and Data Science
✅Discuss data generation from various devices and satellite imagery
✅Mention rapid advances in computer ecosystems and processing capabilities
✅Highlight increasing demand for data science skills
✅Define GIS, data science, and geospatial data science in the introductory chapter
✅Establish a common vernacular for data scientists and GIS professionals
✅Address complex and engaging modern problems
✅Explore topics including GIS, data science, and geospatial data science

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