Summary: The aim of this session of the Sharing knowledge Workshop, is to introduce participants to the data mining and machine learning fields with the minimum of theory and the maximum of activity. Striping the subjects of their inherent complexity participates will explore them by playing with the tools and concentrate on simple tasks (tutorial like), with more curiosity than anxiety for full comprehension. Most of the tools exposed are visual programming interfaces that turn the tasks into a playful, interactive and pedagogic process; also, some simple python code is demonstrated for the sake of illustrating the popular python data science benchwork Anaconda, and some Grasshopper plugins on the field are shown. In the end attendants should get an overview on the data mining field, get some hint on the potential of their use in their work and where to look for further information. Goals: Main: Introduce the participants to data mining process and tools through a hands-on approach. In the end attendants should: understand Rapidminer workflow and its potential; have an overview of data science in Python through the Anaconda package (Jupyter notebooks and Orange3); know the panorama of data mining related tools for Grasshopper.

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Data Mining,Machine learning,Computational design