There are many stars in the sky of open source machine learning frameworks. Last year we talked about Caffe2 and Pytorch, this year they are merged into one framework. The whole framework universe is similarly fast moving.
For many of them it is still unknown if they will burn up quickly or everyone will know their names next year.
For years we have been observing different machine learning frameworks. In this talk we don’t just want to compare the frameworks, we want to go on a historical journey. Where are the roots of the individual frameworks, what is their right to exist and what fun facts can we reveal?
Getting to know machine learning frameworks and their roots.
No experience needed