Lets Make a Question Answering chatbot using the bleeding edge in deep learning (Dynamic Memory Network). We'll go over different chatbot methodologies, then dive into how memory networks work, with accompanying code in Keras.
Code + Challenge for this video:
https://github.com/llSourcell/How_to_make_a_chatbot
Nemanja's Winning Code:
https://github.com/Nemzy/language-translation/blob/master/neural_machine_translation.ipynb
Vishal's Runner up code:
https://github.com/erilyth/DeepLearning-Challenges/tree/master/Language_Translation
Web app to run the code yourself:
https://ethancaballero.pythonanywhere.com
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More Learning resources:
https://www.youtube.com/watch?v=FCtpHt6JEI8&t=643s
https://www.youtube.com/watch?v=Qf0BqEk5n3o&t=637s
https://yerevann.github.io/2016/02/05/implementing-dynamic-memory-networks/
https://www.youtube.com/watch?v=2A5DKPA5lAw
http://www.wildml.com/2016/01/attention-and-memory-in-deep-learning-and-nlp/
https://github.com/domluna/memn2n
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http://wizards.herokuapp.com/
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