In this post I want to explore some of the key similarities and differences between two popular deep learning frameworks: PyTorch and TensorFlow. Why those two and not the others? There are many deep learning frameworks and many of them are viable tools, I chose those two just because I was interested in comparing them specifically. Origins TensorFlow is developed by Google Brain and actively used at Google both for research and production needs. Its closed-source predecessor is called DistBelief. PyTorch is a cousin of lua-based Torch framework which is actively used at Facebook. However, PyTorch is not a simple set of wrappers to support popular language, it was rewritten and tailored to be fast and feel native. The best way to compare two frameworks is to code something up in both of them. I’ve written a companion jupyter notebook for this post and you can get it here . All code will be provided in the post too. First, let’s code a simple approximator for t...
TensorFlow API for .NET languages and tensorflow api for c#