Introduction
This project was part of the Prediction challenge for Data Science for Mobility course taught at DTU in Fall 2020. Description of the challenge is given below
The topic this year is Sustainability in World Cities. At a time when the world is facing unprecedented challenges of different kind, including climate change, pandemics, social inequality, degrading biodiversity, we need to be conscious of the impact and potential of cities as drivers of (positive) change. But what makes a city more sustainable? What best practices exist that could push poor performing cities to improve?
The dataset comes from the “Urban Typologies” project, where 65 indicators that relate to demographics, mobility, economy, city form. can be found This dataset was obtained by combining multiple sources and had the general objective of classifying the different cities of the world according to a typology. It is in itself an interesting Data Sciences exploration.
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