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An LSTM-based model to predict the availability of bike terminals around processing their historical usage data. It was implemented for my Master's thesis in MSc Computer and Systems Engineering at Tallinn University of Technology. The thesis paper itself can be found at https://digikogu.taltech.ee/en/Download/a4145a77-9ba0-4ed8-bd9c-f6ceedc4dfea

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Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
.idea		.idea
dataset_building		dataset_building
prediction_engine/prediction_approaches		prediction_engine/prediction_approaches
.gitignore		.gitignore
README.md		README.md
main.py		main.py

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RealtimePredictionBikeTerminalAvailability

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An LSTM-based model to predict the availability of bike terminals around processing their historical usage data. It was implemented for my Master's thesis in MSc Computer and Systems Engineering at Tallinn University of Technology. The thesis paper itself can be found at https://digikogu.taltech.ee/en/Download/a4145a77-9ba0-4ed8-bd9c-f6ceedc4dfea

python deep-learning keras lstm bike-availability

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