The Chatbot Project in Python is suitable for practice. Anyone who is willing to make a project for their final year submission can leverage the source code.
It can be used by students from Class 11 and 12 to develop a custom project for their submissions. An MTech, BTech or a PhD aspirant can also take reference of this source code for their final year project. Anyone who is willing to create a unique project can use the asset.
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Introduction to chatbot using python
Artificial intelligence is used to construct a computer program known as “a chatbot” that simulates human chats with users. It employs a technique known as NLP to comprehend the user’s inquiries and offer pertinent information. Chatbots have various functions in customer service, information retrieval, and personal support.
A chatbot is a computer program that simulates conversation with humans. Chatbots are often used in customer service applications, where they can answer questions and provide support to customers. Chatbots can also be used for educational purposes, to provide information and answer questions on a variety of topics.
Objectives
Customer service: Many companies are now using chatbots to provide customer support. For example, the chatbot on the American Airlines website can help customers book flights, check their flight status, and get answers to common questions.
Education: Chatbots are also being used in education. For example, the chatbot on the Duolingo website can help students learn new languages.
Sales: Chatbots are also being used in sales. For example, the chatbot on the Drift website can help sales teams qualify leads and answer questions.
Marketing: Chatbots are also being used in marketing. For example, the chatbot on the Sephora website can help customers find the right products and make recommendations.
Entertainment: Chatbots are also being used for entertainment. For example, the chatbot on the Cleverbot website can have conversations with users on a variety of topics.
The main approaches to the development of chatbots are as follows:
Rule-Based Approach: trains a chatbot to answer questions based on a list of pre-determined rules on which it was primarily trained. These set rules can either be pretty simple or quite complex, and we can use these rule-based chatbots to handle simple queries but not process more complicated requests or queries.
Self-learning Chatbots:Self-learning chatbots are chatbots that can learn on their own. These leverage advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML) to train themselves from behaviors and instances. Generally, these chatbots are quite smarter than rule-based bots.
We can classify the Self-learning chatbots furtherly into two categories-
RetrievalBased Models: Based on an input question, these models can obtain predefined responses from a knowledge base. They evaluate user input and compare it to the closest equivalent response in the knowledge base.
Generative Models: Generative models create responses from scratch based on the input query. They employ approaches like sequence-to-sequence models or transformers, for example, to produce human-like answers.
Proposed project
To make a chatbot using Python,
you can use the ChatterBot library. ChatterBot is a Python library that is designed to deliver automated responses to user inputs. It makes use of a combination of ML algorithms to generate many different types of responses. This feature allows you to build chatbots using python that can converse with humans and deliver appropriate and relevant responses.
The ML algorithms help the chatbot to improve its performance with experience.
Another excellent feature of ChatterBot is its language independence. The library is designed in a way that makes it possible to train your chatbot in multiple programming languages.
You can launch a terminal or command prompt. Your machine needs to be configured to run Ai Chatbot Python. To check if this is the case, run the command “python version” or “python3 Version” to ensure it returns a valid Python version.
Installing Chatterbot using the Chatbot Python Package Manager that comes with your Python program. To do this, issue the command “Pip installing chatterbot.” This command will download and install the ChatterBot library and its dependencies.
Once setup is complete, add the following code to your Chatbot using Python script or interactive environment to include Chatterbot: Imported from Chatterbot is ChatBot.
You may now use Chatterbot to begin building your chatbot. Using the ChatterBot guide or other resources, you can learn how to set up and train a chatbot.
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