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by Lak Sri, Muhammad Zain Mustafa, Thanh Lam, Valerie Lampkin
Building Cognitive Applications with IBM Watson Services: Volume 5 Language Translator
Front cover
Notices
Trademarks
Preface
Authors
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Chapter 1. Basics of Watson Language Translator service
1.1 Watson Language Translator service
1.1.1 Authentication
1.1.2 Use case example
1.1.3 Language Translator flow
1.1.4 Code snippets: Node.js and Java
1.2 Language identification
1.2.1 Authenticate
1.2.2 Identify language flow
1.2.3 Node-RED example
1.3 References
Chapter 2. Integrating sentiment analysis and language translationin applications
2.1 Getting started
2.1.1 Objectives
2.1.2 Prerequisites
2.1.3 Expected results
2.2 Architecture
2.3 Two ways to deploy the application: Step-by-step and quick deploy
2.4 Step-by-step implementation
2.4.1 Creating a Node-RED starter application in Bluemix
2.4.2 Creating a Language Translator service instance and connecting itto the Node-RED application
2.4.3 Building the REST language translator flow in Node-RED
2.4.4 Deploying the Node-RED application
2.4.5 Testing the REST call to the Language Translator service
2.5 Quick deployment of application
2.5.1 Deploying the application to Bluemix
2.5.2 Creating a Language Translator service instance and connecting itto the application
2.5.3 Testing the application
2.6 References
Chapter 3. Customizing Language Translator linguistic models
3.1 Introduction
3.2 Custom dictionary
3.3 Expanding the model to improve translation quality
3.4 References
Appendix A. Additional material
Locating the web material
Related publications
IBM Redbooks
Online resources
Help from IBM
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Note: Before using this information and the product it supports, read the information in “Notices” on page v.
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