Simple Chatbot using Python (using Tflearn library)

By Sai Lokesh

It is an NLP model. It is written in Python. This model is built on a simple dataset. Here the dependencies are Nltk and TensorFlow.It's a source code.

It is an NLP model. It is written in Python. This model is built on a simple dataset. Here the dependencies are Nltk and Tensorflow, Tflearn. It is a source code. The code gives an idea about the way to approach building a chatbot. It is a general overview.

First, let's understand what is a chatbot,

A chatbot is a computer program that uses AI to have a conversation with humans. Users can ask the queries and make the requests. The Advanced and best examples of the chatbot are Google Assistant, Alexa, Siri, etc.

Now that the world is moving towards AI, The chatbots became more popular and essential. In many popular services like Railway and Food, we often find Chatbots. In the past, if a customer has any problem they have to contact the service provider through contact number but that method is unreliable. Now with the help of chatbots, we can get the answers to our problems in an instant. Chatbots made life easy.

Now let's understand how they work,

The main technique behind the chatbots is Natural Language Processing(NLP). It is a type of Artificial intelligence that allows computers to break down and understand the human language. First the unnecessary words like as, in, the will be removed from the data. Unnecessary in the sense the words which are not adding any meaning to the sentence. Next, the data will be stemmed. Stemming is the text normalization technique in NLP. With the help of this, the prefix and suffix present in the word will be dropped and only the root word remains. For example, words like sing's, singing, sing will be normalized as a word sing. After that, the letters in the words are divided and encoded with binary numbers.