Data scientists who would like to leverage location-based data and want to use location-based intelligence in the models will benefit from this book considerably. This book is also for GIS Pythonistas who would like to sneak into the magical world of data science and make their analyses more powerful than ever before.
Geospatial Data Science Quick Start Guide
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Geospatial Data Science Quick Start Guide
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Overview of this book
Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses.
This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more.
By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease.
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Geospatial Data Science Quick Start Guide
Table of Contents (9 chapters)
Preface
Free Chapter
Introducing Location Intelligence
Consuming Location Data Like a Data Scientist
Performing Spatial Operations Like a Pro
Making Sense of Humongous Location Datasets
Nudging Check-Ins with Geofences
Let's Build a Routing Engine
Getting Location Recommender Systems
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