Chatbox Machine Learning project

Published on 10 Oct 2020. Written by Amitesh Kumar

An intelligent piece of software which is capable of communicating and gives voice instructions is known as Chatbox. Making a Chatbox is not easy at all as it works on various machine learning concepts. Nowadays, Chatbox has become one of the important parts of machines as it enables a user to communicate directly to the machine. Interaction with the machine consists of voice instructions that the machine can understand. There are basically two types of Chatbox: -

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• Retrieval Based
• Generative Based

As we know, the machine cannot understand the human language but it can compare the words with its dataset to give the output result. The system reads the predefined values and patterns to give the output; this system is known as retrieval-based Chatbox. The Chatbox which is based on deep neural network which facilitate the system to learn the words itself and keep increasing its dataset is known as Generative based Chatbox.

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Project Implementation – Chat box

We will use python language to build this project. The Chatbox will be trained using a special recurrent neural network (LSTM) to identify between user’s messages and then respond accordingly. We will be creating a retrieval based Chatbox using NLTX, Keras, Python, etc. The file which contains the data is the intents.json file which will be included in the project. The data files can easily be downloaded from the internet.  

• First, the data files are imported and loaded to give the project a brain. Json package is loaded in the project.
• Then, the words have to be broken in tokens to give the clear instructions to the machine. This part comes under the preprocessing of the data. For this we will use nltk.word_tokenize () function.
• The duplicating words are removed from the instructions which will facilitate the system to understand the text more clearly. This is known as lemmatizing.
• For the system to work better, we need to create a testing data which will train the system well.
• As the data is ready, the next step will be building of the model which will be of three layers made up of deep learning techniques.
• A graphical user interface is designed for the sake of the user to let them communicate well with the system.
• The final step will be running the program using two main files which are train_chatbot.py and chatpp.py.

The application will use a GUI window to communicate with you for example.

User: - Hello, how are you?

Bot: - I am fine, how can I help.

This is how the conversation will go on. The project is easily implemented using proper files and datasets.

Conclusion

In this java project, the developer should possess a good knowledge over the python programming language. The developer also should know about deep learning concepts and data analytics. The project is highly usable and it has a good market scope as Chatbox are used everywhere. The project should be made with accuracy in order to make the Chatbox intelligent. The bot is implemented in the workflow and this project is a good practice for understanding of python and data manipulation.    

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Kit required to develop Chatbox Machine Learning project:

• No kit required

Technologies you will learn by working on Chatbox Machine Learning project:

• Machine Learning
• Python

Any Questions?