chatbot-Using-LSTM

Chatbot using Seq2Seq LSTM models In this project, we will be using LSTM model using Keras Functional API to build a Chatbot. The potential of chatbot are vast than we can imagine. We can build a chatbot for a rehab process, digital markeing, Personal assitant, in e-commerce sector, & etc. A very fine example of high-end chatbots are the Siri, Alexa & google assistant. In this project We use a special recurrent neural network (LSTM) to classify which category the user’s message belongs to and then we will give a random response from the list of responses.

The six stages involved in building this bot

1. Importing packages
2. Prepocessing the data
3. Building Encoder-Decoder model
4. Training the model
5. Defining Inference model
6. Chat with the bot

There are two basic types of chatbot models based on how they are built:

1. Retrieval Type (A retrieval-based chatbot uses predefined input patterns and responses)&
2. Generative Type (They are based on seq 2 seq neural networks. It is the same idea as machine translation).