Chatbots are computer programs that converse with users, understand their intent, and reply based on preset rules and data. Chatbots are used in dialog systems for various purposes, including customer service, request routing, or information gathering in e-commerce, education, entertainment, finance, health, and more.
The course begins with an in-depth introduction to chatbot basics with ML, DL, and AWS. We will understand chatbots, their needs and types, rule-based/self-learning chatbots and their working mechanisms, and explore ML-based chatbot concepts. We will explore Natural Language Toolkit (NLTK) and install packages to create a corpus with Python. We will train and test the chatbot.
We will then advance to DL-based chatbots and compare conventional with DL-based chatbots. You will learn about tokenization, encoder-decoder, and implementing RNN-based models. Finally, we will explore AWS for chatbot training with DL. We will examine the features of AWS and build a hotel booking chatbot with Amazon Lex. We will connect AWS Lambda to Amazon Lex and integrate the chatbot with Twilio. We will use AWS SDK and create response cards with chatbots.
Upon completion, we will independently be able to build chatbots using ML, DL, and AWS Lex on Python, with a thorough understanding of the creation and functioning of these chatbots.
All resources are available at: https://github.com/PacktPublishing/Chatbots-for-Beginners-A-Complete-Gu…
publication date
2023-02-28
what you will learn
Learn the basic machine learning architecture for the chatbots
Gain hands-on practice in text generation with Python for chatbots
Learn about testing and training chatbots with machine learning
Learn hands-on web-based development of the AWS chatbot
Implement settings of a decoder-encoder model with Python
Understand the impact/overview tokenization in chatbot development
key features
Learn basic ML architecture for chatbots and the impact of ML technology on the chatbots industry * Explore Amazon Web Services (AWS) and the functionality of Amazon Lex for chatbot development * Gain hands-on knowledge of Amazon Lex, Lambda, and Twilio, and their integration with AWS chatbots
approach
The course is crafted to help you understand concepts with real-world applications and provides hands-on experience with a project. This straightforward learning-by-doing course will help you master the concepts and methodology with ease. This course is easy to understand, interactive, self-explanatory, and practical, with live coding with multiple in-depth projects covering complete course content.
audience
This course is designed for individuals looking to advance their skills in applied machine learning and DL, understand relationships of data analysis with ML and DL, learn AWS and apply AWS Lex and Lambda for chatbots, build customized chatbots for their applications, implement DL algorithms for chatbots and rule-based self-learning chatbots. This course can benefit ML/DL practitioners, research scholars, and data scientists researching chatbots. No prior knowledge of chatbots, ML, DL, Amazon Lex, data analysis, or mathematics is required. Prior basic- to intermediate-level Python knowledge is required.
short description
This extensive course for beginners provides the basics of chatbots with machine learning, deep learning, AWS, and its applications, building it from scratch with hands-on practice for chatbot development. This course will help you learn basic to advanced mechanisms of developing chatbots using machine learning, deep learning, and AWS with Python.
subtitle
Develop Chatbots using Machine Learning, Deep Learning, and Amazon Lex
keywords
chatbot, machine learning, deep learning, document-frequency, conventional chatbot, self-learning chatbot, Amazon Lex, Amazon Lambda, Amazon Web Services
Product ISBN
9781837637621
