- It is my final submission for the IBM Data Science Capstone Project, involving extensive exploratory data analysis.
- It uses k-means clustering to cluster the neighborhoods in toronto together (can be generalised to any city).
- Uses knn classification to classify a new neighborhood to a cluster.
- This project also required the use of web scraping, managing dataframes, plotting maps and visualising graphs.
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Predicting the perfect Neighborhood - IBM Data Science Project involving classification, clustering, web scraping, managing dataframes, plotting maps and visualising graphs.
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