Machine Learning on Geographical Data Using Python
- Paperback: 327 pages
- Publisher: WOW! eBook (July 21, 2022)
- Language: English
- ISBN-10: 1484282868
- ISBN-13: 978-1484282861
Machine Learning on Geographical Data Using Python: Introduction into Geodata with Applications and Use Cases
Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data in Python. This book starts with an introduction to geodata and covers topics such as GIS and common tools, standard formats of geographical data, and an overview of Python tools for geodata. Specifics and difficulties one may encounter when using geographical data are discussed: from coordinate systems and map projections to different geodata formats and types such as points, lines, polygons, and rasters. Analytics operations typically applied to geodata are explained such as clipping, intersecting, buffering, merging, dissolving, and erasing, with implementations in Python. Use cases and examples are included. The book also focuses on applying more advanced machine learning approaches to geographical data and presents interpolation, classification, regression, and clustering via examples and use cases.
- Understand the fundamental concepts of working with geodata
- Work with multiple geographical data types and file formats in Python
- Create maps in Python
- Apply machine learning on geographical data
This Machine Learning on Geographical Data Using Python book is your go-to resource for machine learning on geodata. It presents the basics of working with spatial data and advanced applications. Examples are presented using code and facilitate learning by application.