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This week in Kassel, [R]Kenntnistage 2017
took place, organised by EODA
. It was all about Data Science (with R, mostly, as you could guess): Speakers presented interesting applications in industry, manufacturing, ecology, journalism and other fields, including use cases such as predictive maintenance, forecasting and risk analysis.
I had the honour to have a talk too (thanks guys!), combining two of my favorite topics – deep learning and R. The slides are on RPubs as usual, and the source code (including complete examples) can be found on github.
Last not least, it’s great to see data science, and R, gaining momentum like that (this is Europe, so I can still write such a sentence ;-))
If you allow me to include an advertisement here – if you’re wondering what insight might come out of your data: At Trivadis, we’re a (yet) smallish but super motivated team of data scientists and machine learning practitioners happy to help!
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