Almost all of us use whatsapp on a daily basis. Those conversations are basically unstructured text that we can use in order to learn and experiment. In this tutorial I will show how to create a very simple chatbot, that you can chat with, simply by training a doc2vec model using all the messages you already have on you phone.

Disclaimer: This post and implementation is based on the following great post which appeared in toward-data-science

If you’re just interested in the full python notebook, it’s right here (I changed the original names)

At a high level, the steps would include:

• Loading your whatsapp conversation into a python DataFrame
• Preparing a training set of (text, response) tuples – so the chatbot will be able to respond to your input
• Training a Doc2Vec model
• Implementing the chatbot conversation in python

Let’s start…

Representing unstructured documents as vectors can be done in many ways. One very common approach is to use the well-known word2vec algorithm, and generalize it to documents level, which is also known as doc2vec.

A great python library to train such doc2vec models, is Gensim. And this is what this tutorial will show.

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