Machine Learning on Geographical Data Using Python: Introduction into Geodata with Applications and Use Cases

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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. This 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 (accessible at github.com/Apress/machine-learning-geographic-data-python) and facilitate learning by application.

What You Will Learn

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

Who This Book Is For
Readers with a basic understanding of machine learning who wish to extend their skill set to analysis of and machine learning on spatial data while remaining in a common data science Python environment

Format

Digital book

SKU

Not available

Publisher

Not available

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Product details

Publisher ‏ : ‎ Apress; 1st ed. edition (July 21, 2022)
Language ‏ : ‎ English
Paperback ‏ : ‎ 327 pages
ISBN-10 ‏ : ‎ 1484282868
ISBN-13 ‏ : ‎ 978-1484282861
Item Weight ‏ : ‎ 1.38 pounds
Dimensions ‏ : ‎ 7 x 0.75 x 10 inches

Best Sellers Rank: #2,698,701 in Books (See Top 100 in Books)
- #781 in Artificial Intelligence (Books)
- #2,621 in Python Programming
- #2,632 in Computer Programming Languages

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