This Thursday we will have a more casual Data Science Night revolving around the Keras library for deep-learning, and its implementations in Python and R.
Keras was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research (www.keras.io).
We'll start with some socializing before running through a few tutorials. Afterwards, we'll break out into small groups to continue exploring the night's topic or work on other projects. Bring your laptops if you want to follow along.
We recommend installing Jupyter or R Markdown beforehand. (guide: http://www.data-science-nights.org/getting-started-with-data-science.html).
Further, please install Keras together with one of its backend engines ( guide for Python: https://keras.io; guide for R: https://tensorflow.rstudio.com/keras/reference/install_keras.html )
(credit of picture: pexels / pixabay)