Building Cognitive Applications with IBM Watson Services: Volume 4 Natural Language Classifier

Marcelo Mota Manhaes · Taemin Ko · Abeer Selim · Omar Amer · Lak Sri · IBM Redbooks

2017年5月 · IBM Redbooks

關於這本電子書

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 4, introduces the Watson Natural Language Classifier service. This service applies cognitive computing techniques to return best matching predefined classes for short text inputs such as a sentence or phrase. The book describes concepts that you need to understand to create, use and train the classifier. This book describes how to prepare training data, and create and train the classifier to connect the classes to example texts so the service can apply the classes to new inputs. It provides examples of applications that demonstrate how to use the Watson Natural Language Classifier service in practical use cases. You can develop and deploy the sample applications 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.