Jake VanderPlas • 7/23/2015

Learning Seattle's Work Habits from Bicycle Counts

This technical article revisits Seattle's Fremont Bridge bicycle count data, applying unsupervised machine learning techniques like PCA and Gaussian Mixture Models in Python (using Pandas, Matplotlib, and Scikit-learn) for data exploration. It demonstrates how to extract insights about aggregate work habits of bicycle commuters from the data, contrasting with a previous supervised learning approach.

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#Python #Pandas #Scikit Learn