Summary
TUM will contribute their existent data loaders interfaces and wrapper functions helping SINERGISE to accelerate the development of ML gateways towards external ML frameworksThe exact list of ML frameworks will be fixed after the data modelling requirements will be finalised Current list of potential ML frameworks to be integrated consists ofTENSORFLOW Googles TensorFlow is the most widely used framework for machine learning based on Theano see below KERAS is an open source neural network library written in Python It is designed to enable fast experimentation with deep neural networks it focuses on being userfriendly modular and extensible APACHE MXNet is a modern opensource machine learning framework used to train and deploy deep neural networksPyTorch primarily developed by Facebooks AI Research lab FAIR is free and opensource software ermarked by two highlevel features Tensor computing and Deep neural networks
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