Chatbot using python machine learning | part 5 Building Inference Model | Predicting from seq2seq

Today in this part we have built Inference model for our Chatbot model/ seq2seq model for predictions.
Inference model is a model used to make predictions from our encoder decoder model.
We used simple encoder decoder model to train our chatbot
We haven't used attention yet but in later video we might build attention too.


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code in this video : https://github.com/Pawandeep-prog/chatbot
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? you might find some errors while running the code shown in video that's all my fault I'm sorry for that.
so that's why I've uploaded another no error code above ? I'll soon make video on that


so keep subscribed for more videos.

In this series we are building a chatbot from scratch and step by step and using cornell movie dataset for that.we use seq2seq encoder decoder model and we will use keras functional approach to build this model.

Playlist : https://www.youtube.com/playlist?list=PLTuKYqpidPXbulRHl8HL7JLRQXwDlqpLO

STAY TUNED FOR MORE VIDEOS. ?


*** Readings ****
embedding : https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/

return sequences vs return state : https://machinelearningmastery.com/return-sequences-and-return-states-for-lstms-in-keras/


code on github : https://github.com/Pawandeep-prog/keras-seq2seq-chatbot-with-attention code on

kaggle : https://www.kaggle.com/programminghut/new-chatbot

dataset : https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html

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Atlast if you have any queries or error in your installation feel free to ask them in below comment section.

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