This repository contains code and jupyter notebooks with machine learning algorithms for working with GPS trajectories. It will be used during the Machine Learning hackathon of IotTechDay2017.
The dataset used is the popular GeoLife GPS Trajectories
We have already processed this dataset, so that each trajectory (which only contains lat, long, timestamp) is enriched with velocity, acceleration and modality information.
This processed data can be downloaded from google drive (size 3.7 GB). It is also available in zipped format (size 0.9 GB)
For the classification and clustering part, only the metadata files are necessary. These contain aggregated data per trajectory (such as average velocity, average acceleration etc). These metadata files are much smaller in size and can be downloaded from google drive (1.5 MB zipped) and dropbox (3.6 MB unzipped)
We have provided some notebooks, which should give you a flying start, but feel free to do everything your own way.
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