In this series, I’m experimenting with Natural Language Processing, specifically with Word Generation using Python and Tensorflow! Watch as we write the functions to process the input (In this case, a bunch of text files that have all written works by Edgar Allan Poe) and then train a model to predict a “next character” given a sequence of characters.
Tensorflow provides some really fun tools that can be used to do all sorts of interesting programming tasks, and this is just a small sample of it’s power. But I think it’s cool to learn and hopefully this series gives you a good, small foundation for python and tensorflow.
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In this video, I go over how to process the text input, how we build a Tensorflow model with the keras package, how we convert that text into numbers that the model can use to train itself, and then how we use a built model to actually generate text! The model used in this series is a Recurrent Neural Network (RNN) with two LSTM layers, with ReLu activation functions.
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