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.
🔴 Link to Episode 1!
• How to Create a Word Generator with T...
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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.
🕘Timestamps:
0:30 Covering our functions from last time
05:39 - Talking about what we're doing in this video
07:55 - How to build a function that trains our RNN model
35:30 - Fixing our model input mistake (Used the full character array instead of the character vocabulary)
54:50 - How to build a function that generates text from our RNN
01:06:10 - Outro
Thanks for watching! I plan on making a ton more tutorial programming videos on libraries I find interesting, and if that’s your sort of thing, check out my other videos and subscribe for more. Thanks!
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