Buch, Englisch, 385 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 616 g
Work with Protected Enterprise Data Using Open Source Frameworks
Buch, Englisch, 385 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 616 g
ISBN: 978-1-4842-5033-4
Verlag: Apress
In the next sections, you'll design and implement the backend framework of a typical chatbot from scratch. You will also explore some popular open-source chatbot frameworks such as Dialogflow and LUIS. The authors then explain how you can integrate various third-party services and enterprise databases with the custom chatbot framework. In the final section, you'll discuss how to deploy the custom chatbot framework on the AWS cloud.
By the end of Building an Enterprise Chatbot, you will be able to design and develop an enterprise-ready conversational chatbot using an open source development platform to serve the end user.
What You Will Learn - Identify business processes where chatbots could be used
- Focus on building a chatbot for one industry and one use-case rather than building a ubiquitous and generic chatbot
- 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
Who This Book Is ForData scientists and enterprise architects who are currently looking to deploy chatbot solutions to their business.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Betriebssysteme Linux Betriebssysteme, Open Source Betriebssysteme
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
Weitere Infos & Material
Chapter 1: Processes in the Banking and Insurance Industry.- Chapter 2: Identifying the Sources of Data.- Chapter 3: Mining Intents from the Data Sources.- Chapter 4: Building a Business Use-Case.- Chapter 5: Natural Language Processing (NLP).- Chapter 6: Building Chatbots Using Popular Platforms.- Chapter 7: Chatbot Platforms.- Chapter 8: Chatbot Integration Mechanism.- Chapter 9: Deployment and Continuous Improvement Framework.