Beeswarm plot with the SHAP values for every variable. by Jocelyn Tapia (20934049)

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Waterfall plots for houses in different municipalities. by Jocelyn Tapia (20934049)

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Dependence plots for amenity and image variables. by Jocelyn Tapia (20934049)

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Choropleth maps of the municipalities of the Metropolitan Region. by Jocelyn Tapia (20934049)

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Dependence plots for distance variables. by Jocelyn Tapia (20934049)

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Hedonic prices as tangencies between attributes demanded and offered [10]. by Jocelyn Tapia (20934049)

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Dependence plots for two variables. by Jocelyn Tapia (20934049)

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Data Sheet 1_Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning.pdf by Max Anjos (20517458)

“…Here, we introduce a ML-based bottom-up framework to predict hourly CO₂ emissions from vehicular traffic at fine spatial resolution (30 × 30 m). Using data-driven algorithms, traffic counts, spatio-temporal features, and meteorological data, our model predicted hourly traffic flow, average speed, and CO₂ emissions for passenger cars (PC) and heavy-duty trucks (HDT) at the street scale in Berlin. …”