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citypulse-city-dashboard

The CityPulse framework provides immediate and intuitive visual access to the results of its intelligent processing and manipulation of data and events. The ability to record and store historical (cleaned and summarized) data for post-processing makes it possible to analyse the status of the city not only on the go but also at any point in time, enabling diagnosing and “post mortem” analysis of any incidents or relevant situation that might have occurred. To facilitate that, a dashboard for visualising the dynamic data of the smart cities is provided on top of the CityPulse framework.

gpsmachinelearning

graph-representation-learning-tutorial

Code for Data61's tutorial on Graph Representation Learning

idcf

orange

Orange 2 (Python 2.7) data mining suite http://orange.biolab.si

predict-remaining-useful-life

Predict remaining useful life of a component based on historical sensor observations using automated feature engineering

pybrain

taxi-trajectories

traclus_impl

Python implementation of Traclus algorithm, for 2-D trajectories