Tag: Rnn rss

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06 December 2017 /
Understanding the shape of your model is sometimes non-trivial when it comes to machine learning. Look at convolutional neural nets with the number of filters, padding, kernel sizes etc and it’s quickly evident why understanding what shapes your inputs and outputs are will keep you sane and reduce the time spent digging into strange errors. TensorFlow’s RNN API exposed me to similar frustrations and misunderstandings about what I was expected to give it and what I was getting in return.