Basics of chatbots with machine learning & Python.

Chatbots are software applications used for online chat conversations through text or text-to-speech instead of providing direct contact with a live human agent. Chatbots are used in dialog systems for various purposes, including customer service, request routing, or information gathering. This cour...

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Format: Video
Language:English
Published: [Place of publication not identified] : Packt Publishing, 2023.
Edition:[First edition].
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Online Access:Click for online access

MARC

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520 |a Chatbots are software applications used for online chat conversations through text or text-to-speech instead of providing direct contact with a live human agent. Chatbots are used in dialog systems for various purposes, including customer service, request routing, or information gathering. This course begins with a brief overview of chatbots, their need, and the types of chatbots. We will explore rule-based versus self-learning chatbots. We will understand the working mechanism of chatbots. We will explore machine learning-based chatbots and understand the ML-based architecture of chatbots. You will learn about the purpose of ML-based chatbots and their impact. We will get an overview of the Natural Language Toolkit (NLTK). You will learn to install packages and create a corpus with Python. We will delve into text preprocessing and helper function deployment, generate responses, and implement term-frequency times inverse document-frequency. We will train and test rule-based chatbots and finally work on a project developing an artificial intelligence question-answer chatbot using NLTK. Upon course completion, you will be able to relate the concepts and theories for chatbots in various domains, understand and implement machine learning models for building real-time chatbots, and evaluate machine learning models in chatbots. What You Will Learn Learn about chatbot types, rule-based and self-learning chatbots Learn text preprocessing and develop helper functions with Python Explore the impact and overview of the Natural Language Toolkit Gain hands-on practice, generate text in Python to develop chatbots Explore testing and training of chatbot with machine learning Implement term-frequency times inverse document-frequency hands-on Audience This course delivers content to people wishing to advance their skills in applied machine learning, master data analysis with machine learning, build customized chatbots for their applications, and implement machine learning algorithms for chatbots. This course is for you if you are passionate about rule-based and conversational chatbots. Machine learning practitioners, research scholars, and data scientists can benefit from the course. No prior knowledge of chatbots, or machine learning, is needed. You will need to know basic to intermediate Python coding, which is not taught separately in the course. About The Author AI Sciences: AI Sciences is a group of experts, PhDs, and practitioners of AI, ML, computer science, and statistics. Some of the experts work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. They have produced a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of machine learning, statistics, artificial intelligence, and data science. Initially, their objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory. Today, they also publish more complete courses for a wider audience. Their courses have had phenomenal success and have helped more than 100,000 students master AI and data science. 
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