Build Your First Chatbot With Python and Integrate It on Telegram

Build Your First Chatbot With Python and Integrate It on Telegram

Using Python’s Natural Language Toolkit. “Chatbots can cut operational costs by up to 30%. eCommerce chatbot statistics show that businesses spend around $1.3 trillion on customer requests per year. With the assistance of chatbots, this expense could be reduced by 30%.” — The Future is Now — 37 Fascinating Chatbot Statistics by Danica Jovic

“Chatbots can cut operational costs by up to 30%. eCommerce chatbot statistics show that businesses spend around $1.3 trillion on customer requests per year. With the assistance of chatbots, this expense could be reduced by 30%.” — [The Future is Now — 37 Fascinating Chatbot Statistics_](https://www.smallbizgenius.net/by-the-numbers/chatbot-statistics/#gref) by Danica Jovic_

A few days back, I attended an online workshop from The MAD — Alpha where I got to learn about the development and deployment of various types of chatbots, like data-driven chatbots, machine learning chatbots, and a very robust chatbot through Rasa Framework. In this article, I am going to share the terminology involved while developing a chatbot and show you how to develop a data-driven chatbot and deploy it on Telegram.


What Is a Chatbot?

At an essential level, a chatbot is a PC program that recreates and forms human conversation, permitting people to collaborate with computerized gadgets as though they were speaking with a genuine person. Chatbots can be as simple as that answer to a basic query with a single line reaction, or as advanced as a computerized assistant that learns and develops to respond to expanding levels of personalization as they assemble and process data (or, we can say, a machine learning bot).

Some of the ways companies are using chatbots are:

  • As customer support
  • Booking the items from a business

Types of chatbots

There are mainly two types of chatbots:data-driven chatbots and contextual chatbots.

  • In a data-driven chatbot, the bot analyzes the keywords from the user question and matches the keywords with the predetermined options to deliver the correct response. These are implemented with NLTK (Natural Language Toolkit)library in Python.
  • A contextual chatbot is much more advanced. It simulates near-human interactions better than a data-driven chatbot because when a user types a question, the bot tries to learn the intent and sentiment behind the user’s query. These chatbots utilize machine learning to learn and advance over time.

In this article, we will build a data-driven chatbot based on the NLTK library in Python and deploy it on Telegram so as to converse with our bot.


Prerequisites and Terminologies for Chatbots

Prerequisites

Basic knowledge of Python is sufficient for anyone who wants to make this chatbot.

NLP

Natural language processing assists computers to communicate with people in their language and scales other language-related assignments. For instance, NLP makes it feasible for computers to understand text, to hear speech and interpret it, to measure conclusions, and to figure out which parts are significant. By using NLP, developers can perform tasks such as text summarization, named-entity relationship, sentiment analysis, and speech recognition.

python chatbots programming machine-learning nlp

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