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Geospatial Data Science Quick Start Guide

You're reading from   Geospatial Data Science Quick Start Guide Effective techniques for performing smarter geospatial analysis using location intelligence

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789809411
Length 170 pages
Edition 1st Edition
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Authors (2):
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Abdishakur Hassan Abdishakur Hassan
Author Profile Icon Abdishakur Hassan
Abdishakur Hassan
Jayakrishnan Vijayaraghavan Jayakrishnan Vijayaraghavan
Author Profile Icon Jayakrishnan Vijayaraghavan
Jayakrishnan Vijayaraghavan
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Summary

In this chapter, we explored different types of recommenders. In the first section, we did an exploratory data analysis to get a grasp of the dataset. We also preprocessed and cleaned a dataset, as well as merged different DataFrames. In the second section, we learned about collaborative filtering recommenders and used two different algorithms. In the final section, we explored LB recommenders and used the k-means clustering algorithm and top-rated restaurants to recommend restaurant venues based on the location of the user.

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