Download or read book Building Cognitive Applications with IBM Watson Services: Volume 5 Language Translator written by Valerie Lampkin and published by IBM Redbooks. This book was released on 2017-05-25 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 5, describes how the Watson Language Translator service can be used to translate text from one language to another. It introduces the concepts that you need in order to understand how to use the Watson Language Translator service. It provides an example of an application that integrates the Watson Language Translator service. You can develop and deploy the sample application by following along in a step-by-step approach and using provided code snippets. Alternatively, you can download an existing Git project to more quickly deploy the application. This book also covers a mechanism provided by the Watson Language Translator service to train the service to perform domain-specific translations by customizing the existing linguistic models.