During the journal club of next month's meeting (14/07/17) I will be running through an example application of Keras, a popular library for neural networks in python. Specifically, the tutorial takes the form of a Jupyter Notebook, and will cover: reading in data from ROOT files, data pre-processing, MVA training, ensembling, testing, and application.
The tutorial is available at https://github.com/GilesStrong/ML_Tutorials. Due to the runtime, I'd recommend that anyone wishing to follow the tutorial try to run the notebook in advance. There will probably be some software installation required too. Any problems, questions, or compatibility issues, don't hesitate to contact me.
In order to read in the ROOT files, you must have configured your ROOT installation to include python (which might not be default). If there are problems, or you don't want to reconfigure ROOT, I can make the data available in CSV.
