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Building an enterprise chatbot : work with protected enterprise data using open source frameworks /

Explore the adoption of chatbots in business by focusing on the design, deployment, and continuous improvement of chatbots in a business, with a single use-case from the banking and insurance sector. This book starts by identifying the business processes in the banking and insurance industry. This i...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Singh, Abhishek, 1976- (Autor), Ramasubramanian, Karthik (Autor), Shivam, Shrey (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Apress, [2019]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:Explore the adoption of chatbots in business by focusing on the design, deployment, and continuous improvement of chatbots in a business, with a single use-case from the banking and insurance sector. This book starts by identifying the business processes in the banking and insurance industry. This involves data collection from sources such as conversations from customer service centers, online chats, emails, and other NLP sources. Youll then design the solution architecture of the chatbot. Once the architecture is framed, the author goes on to explain natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) with examples. In the next section, youll discuss the importance of data transfers using natural language platforms, such as Dialogflow and LUIS, and see why this is a key process for chatbot development. In the final section, youll work with the RASA and Botpress frameworks. By the end of Building an Enterprise Chatbot with Python, you will be able to design and develop an enterprise-ready conversational chatbot using an open source development platform to serve the end user. You will: Identify business processes Design the solution architecture for a chatbot Integrate chatbots with internal data sources using APIs Discover the differences between natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) Work with deployment and continuous improvement through representational learning.
Descripción Física:1 online resource : illustrations
Bibliografía:Includes bibliographical references and index.
ISBN:9781484250341
1484250346
1484250338
9781484250334
9781484250358
1484250354