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Wondering what Tensorflow has to do with that out-performance since it must be all about the model/algorithm that you implemented in that - like you could've had a TF code running the same conventional approach you mentioned above - which wouldn't have done any magic. Isn't it the algorithm like a convnet doing the magic rather than TF itself responsible for it?


Yes, TF is merely a framework implementing convolutional neural nets, not a novel implementation of them.

We chose TF over other convolutional neural net libraries because it was 1. Python and 2. heavily sponsored by Google.




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