We're back to our discussion format so there will be no presentation this month. Instead be prepared to share your insights and experiences on 1) privacy and ML and 2) The Fast.AI library.
Privacy for ML is a big topic so we'll start by reviewing the PySyft project, paper and tutorials. PySyft is a Python library for secure, private Deep Learning. PySyft decouples private data from model training, using Multi-Party Computation (MPC) within PyTorch. Links to materials are at: https://github.com/OpenMined/PySyft/tree/master/examples/tutorials
Fast.ai is a company dedicated to making the power of deep learning accessible to all. They've done this with their live courses at Unisversity of San Francisco, the corresonding free online MOOC, many free talks and presentations, and a deep learning framework built on top of PyTorch. I've heard many good things about the framework so lets dig into it and discuss it at the meeting. More info at: https://docs.fast.ai
Note the doors will be locked. Please try to arrive by 6:15 and reach me on twitter, @JulioBarros, if you have any questions or need to be let in. Thanks.