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You're reading from  Conversational AI with Rasa

Product typeBook
Published inOct 2021
PublisherPackt
ISBN-139781801077057
Edition1st Edition
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Authors (2):
Xiaoquan Kong
Xiaoquan Kong
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Xiaoquan Kong

Xiaoquan is a machine learning expert specializing in NLP applications. He has extensive experience in leading teams to build NLP platforms in several Fortune Global 500 companies. He is a Google developer expert in Machine Learning and has been actively involved in contributions to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stage and became a Rasa Superhero in 2018. He manages the Rasa Chinese community and has also participated in the Chinese localization of TensorFlow documents as a technical reviewer.
Read more about Xiaoquan Kong

Guan Wang
Guan Wang
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Guan Wang

Guan is currently working on Al applications and research for the insurance industry. Prior to that, he was a machine learning researcher at several industry Al labs. He was raised and educated in Mainland China, lived in Hong Kong for 10 years before relocating to Singapore in 2020. Guan holds BSc degrees in Physics and Computer Science from Peking University, and an MPhil degree in Physics from HKUST. Guan is an active tech blogger and community contributor to open source projects including Rasa, receiving more than10,000 stars for his own projects on Github.
Read more about Guan Wang

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What this book covers

Chapter 1, Introduction to Chatbots and the Rasa Framework, introduces all the fundamental knowledge pertaining to chatbots and the Rasa framework, including machine learning, NLP, chatbots, and Rasa Basic.

Chapter 2, Natural Language Understanding in Rasa, covers Rasa NLU’s architecture, configuration methods, and how to train and infer.

Chapter 3, Rasa Core, introduces how to implement dialogue management in Rasa.

Chapter 4, Handling Business Logic, explains how Rasa gives developers great flexibility in handling different business logic. This chapter introduces how we can use these features to handle complex business logic more elegantly and efficiently.

Chapter 5, Working with Response Selector to Handle Chitchat and FAQs, explains how to define questions and their corresponding answers and how to configure Rasa to automatically identify the query and give the corresponding answer.

Chapter 6, Knowledge Base Actions to Handle Question Answering, describes how to create a knowledge base that will be used to answer questions. You will also learn to customize knowledge base actions, learn how referential resolution (mapping mention to object) works, and how to create your own knowledge base.

Chapter 7, Entity Roles and Groups for Complex Named Entity Recognition, explains how entity roles and entity groups solve the complex NER problem, and how to define training data, configure pipelines, and write stories for entity roles and entity groups.

Chapter 8, Working Principles and Customization of Rasa, introduces the working principles behind Rasa and how we can extend and customize Rasa.

Chapter 9, Testing and Production Deployment, explains how to test Rasa applications and how to deploy Rasa applications in production environments.

Chapter 10, Conversation-Driven Development and Interactive Learning, introduces conversation-driven development and Rasa X to develop chatbots more effectively. We will also introduce how to use interactive learning to quickly find and fix problems.

Chapter 11, Debugging, Optimization, and Community Ecosystem, explains how to debug and optimize Rasa applications. We will also introduce some tools to help developers build chatbots effectively.

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Conversational AI with Rasa
Published in: Oct 2021Publisher: PacktISBN-13: 9781801077057

Authors (2)

author image
Xiaoquan Kong

Xiaoquan is a machine learning expert specializing in NLP applications. He has extensive experience in leading teams to build NLP platforms in several Fortune Global 500 companies. He is a Google developer expert in Machine Learning and has been actively involved in contributions to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stage and became a Rasa Superhero in 2018. He manages the Rasa Chinese community and has also participated in the Chinese localization of TensorFlow documents as a technical reviewer.
Read more about Xiaoquan Kong

author image
Guan Wang

Guan is currently working on Al applications and research for the insurance industry. Prior to that, he was a machine learning researcher at several industry Al labs. He was raised and educated in Mainland China, lived in Hong Kong for 10 years before relocating to Singapore in 2020. Guan holds BSc degrees in Physics and Computer Science from Peking University, and an MPhil degree in Physics from HKUST. Guan is an active tech blogger and community contributor to open source projects including Rasa, receiving more than10,000 stars for his own projects on Github.
Read more about Guan Wang