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Conversational AI with Rasa: Build, test, and deploy AI-powered, enterprise-grade virtual assistants and chatbots
Create next-level AI assistants and transform how customers communicate with businesses with the power of natural language understanding and dialogue management using Rasa
Key FeaturesUnderstand the architecture and put the underlying principles of the Rasa framework to practiceLearn how to quickly build different types of chatbots such as task-oriented, FAQ-like, and knowledge graph-based chatbotsExplore best practices for working with Rasa and its debugging and optimizing aspectsBook DescriptionThe Rasa framework enables developers to create industrial-strength chatbots using state-of-the-art natural language processing (NLP) and machine learning technologies quickly, all in open source.
Conversational AI with Rasa starts by showing you how the two main components at the heart of Rasa work – Rasa NLU (natural language understanding) and Rasa Core. You'll then learn how to build, configure, train, and serve different types of chatbots from scratch by using the Rasa ecosystem. As you advance, you'll use form-based dialogue management, work with the response selector for chitchat and FAQ-like dialogs, make use of knowledge base actions to answer questions for dynamic queries, and much more. Furthermore, you'll understand how to customize the Rasa framework, use conversation-driven development patterns and tools to develop chatbots, explore what your bot can do, and easily fix any mistakes it makes by using interactive learning. Finally, you'll get to grips with deploying the Rasa system to a production environment with high performance and high scalability and cover best practices for building an efficient and robust chat system.
By the end of this book, you'll be able to build and deploy your own chatbots using Rasa, addressing the common pain points encountered in the chatbot life cycle.
What you will learnUse the response selector to handle chitchat and FAQsCreate custom actions using the Rasa SDKTrain Rasa to handle complex named entity recognitionBecome skilled at building custom components in the Rasa frameworkValidate and test dialogs end to end in RasaDevelop and refine a chatbot system by using conversation-driven deployment processingUse TensorBoard for tuning to find the best configuration optionsDebug and optimize dialogue systems based on RasaWho this book is forThis book is for NLP professionals as well as machine learning and deep learning practitioners who have knowledge of natural language processing and want to build chatbots with Rasa. Anyone with beginner-level knowledge of NLP and deep learning will be able to get the most out of the book.
Table of ContentsIntroduction to Chatbots and the Rasa FrameworkNatural Language Understanding in RasaRasa CoreHandling Business LogicWorking with Response Selector to Handle chitchat and FAQsKnowledge Base Actions to Handle Question AnsweringEntity Roles and Groups for Complex Named Entity RecognitionCustomization of RasaTesting and Production DeploymentConversation-Driven Development and Interactive LearningDebugging, Optimization, and the Community Ecosystem
Key FeaturesUnderstand the architecture and put the underlying principles of the Rasa framework to practiceLearn how to quickly build different types of chatbots such as task-oriented, FAQ-like, and knowledge graph-based chatbotsExplore best practices for working with Rasa and its debugging and optimizing aspectsBook DescriptionThe Rasa framework enables developers to create industrial-strength chatbots using state-of-the-art natural language processing (NLP) and machine learning technologies quickly, all in open source.
Conversational AI with Rasa starts by showing you how the two main components at the heart of Rasa work – Rasa NLU (natural language understanding) and Rasa Core. You'll then learn how to build, configure, train, and serve different types of chatbots from scratch by using the Rasa ecosystem. As you advance, you'll use form-based dialogue management, work with the response selector for chitchat and FAQ-like dialogs, make use of knowledge base actions to answer questions for dynamic queries, and much more. Furthermore, you'll understand how to customize the Rasa framework, use conversation-driven development patterns and tools to develop chatbots, explore what your bot can do, and easily fix any mistakes it makes by using interactive learning. Finally, you'll get to grips with deploying the Rasa system to a production environment with high performance and high scalability and cover best practices for building an efficient and robust chat system.
By the end of this book, you'll be able to build and deploy your own chatbots using Rasa, addressing the common pain points encountered in the chatbot life cycle.
What you will learnUse the response selector to handle chitchat and FAQsCreate custom actions using the Rasa SDKTrain Rasa to handle complex named entity recognitionBecome skilled at building custom components in the Rasa frameworkValidate and test dialogs end to end in RasaDevelop and refine a chatbot system by using conversation-driven deployment processingUse TensorBoard for tuning to find the best configuration optionsDebug and optimize dialogue systems based on RasaWho this book is forThis book is for NLP professionals as well as machine learning and deep learning practitioners who have knowledge of natural language processing and want to build chatbots with Rasa. Anyone with beginner-level knowledge of NLP and deep learning will be able to get the most out of the book.
Table of ContentsIntroduction to Chatbots and the Rasa FrameworkNatural Language Understanding in RasaRasa CoreHandling Business LogicWorking with Response Selector to Handle chitchat and FAQsKnowledge Base Actions to Handle Question AnsweringEntity Roles and Groups for Complex Named Entity RecognitionCustomization of RasaTesting and Production DeploymentConversation-Driven Development and Interactive LearningDebugging, Optimization, and the Community Ecosystem
264 pages, Kindle Edition
Published October 8, 2021
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8 people want to read
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Displaying 1 - 2 of 2 reviews
September 14, 2023
O livro pontua conceitos importantes desde a arquitetura padrão de chatbot até customizações na framework. O que me faz não dar 4 estrelas são as repetições excessivas de explicações, colocar algumas configurações nas áreas de código que não são explicadas, e o capítulo sobre deploy poderia ter sido mais elaborado. Mesmo com esses pontos, ele consegue instruir do básico ao intermediário.
February 14, 2023
Since now Rasa is on version 3x, the book is less relevant hence 4 stars. The documentation has much more up to date examples now. Rasa X is no longer supported in the format in the book either. Still a good reference though for someone like me who wasn't aware about Rasa at all before
Displaying 1 - 2 of 2 reviews