Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
-
Updated
Apr 9, 2019 - Python
Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
Python library to get information about houses from pararius.nl
Full-stack web application for the visualization of road attributes and route planning in Amsterdam using area avoidance, focusing on the needs of the elderly and vulnerable people
University Course Timetabling Problem using different algorithms, part of the Algorithms and Heuristics course at the University of Amsterdam.
NLP pipeline for extracting insights related to venue accessibility in Amsterdam.
The aim of this full-stack project is to predict with RandomForest and visualize crowdedness for metro stations of Amsterdam by using external factors.
Repertorium van notarissen 1524 - 1810
The Amsterdam Corporate Group Portraits dataset contains biographical information on persons depicted on institutional/corporate group portraits in the seventeenth and eighteenth century in Amsterdam. The dataset is part of the Golden Agents project.
Developments and findings of the Golden Agents (https://www.goldenagents.org/) Processes of Creativity case study
Kohier van de 200ste penning, Amsterdam 1674
Vector maps of the Amsterdam Waterlooplein neighbourhood between 1800 en 2000 in GeoJson
Add a description, image, and links to the amsterdam topic page so that developers can more easily learn about it.
To associate your repository with the amsterdam topic, visit your repo's landing page and select "manage topics."