Basics of Chatbots with Machine Learning & Python

Overview

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This course offers a thorough exploration of chatbots and their development using machine learning and Python. You’ll start with an introduction to chatbots, including their history and various applications across industries. The course then delves into the distinctions between chatbots, virtual assistants, and personal assistants, providing a comprehensive overview of their respective benefits and challenges. As you progress, you’ll focus on machine learning-based chatbots, exploring their architecture, features, and the revolutionary impact of ML on customer service, healthcare, and more. You’ll gain practical experience by working with the Natural Language Toolkit (NLTK) to develop rule-based chatbots, covering essential topics such as data input, word tokenization, lemmatization, and response generation. The course also covers advanced concepts like Wikipedia search integration and local search mechanisms, enabling you to build more robust and interactive chatbots. Finally, you will apply everything you’ve learned in a project where you develop a conversational chatbot from scratch. You’ll handle data collection, preprocessing, and response generation using sophisticated techniques like TF-IDF and cosine similarity. By the end, you’ll have a fully functional chatbot and a deep understanding of the principles and practices of chatbot development, positioning you to leverage AI in real-world applications. This course is ideal for software developers, data scientists, and AI enthusiasts who want to build chatbots using machine learning and Python. A basic understanding of Python programming is required, and familiarity with machine learning concepts will be beneficial but not mandatory.

Syllabus

Introduction

In this module, we will introduce the course, outlining the instructor’s credentials and AI Sciences' expertise. We’ll also provide a brief overview of the course structure and delve into key chatbot technologies, including machine learning-based and conversational chatbots.

Overview of Chatbots

In this module, we will explore the origins of chatbots, their advancements, and their modern-day uses. You'll learn how chatbots differ from virtual and personal assistants, and investigate the various types, benefits, and challenges associated with them.

Machine Learning-Based Chatbots

In this module, we will dive into machine learning-powered chatbots, covering their architecture and the critical role of the Natural Language Toolkit (NLTK) in development. You'll gain hands-on experience building a rule-based chatbot, learning about various ML features that enhance chatbot performance.

Project: Conversational Chatbot Development with Machine Learning

In this module, we will guide you through a complete project, where you’ll develop a conversational chatbot using the NLTK library. From gathering data to creating intelligent responses, you’ll build and test a fully functioning chatbot capable of engaging users in conversation.