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

by Marcelo Mota Manhaes, Taemin Ko, Abeer Selim, Omar Amer, Lak Sri

May 2017

Intermediate to advanced

142 pages

3h 4m

English

IBM Redbooks

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1.1 Using the Natural Language Classifier service1.1.1 Prepare training data1.1.2 Create and train the classifier1.1.3 Query the trained classifier1.1.4 Evaluate results and update the data1.2 References
2.1 Requirements2.2 Creating the Natural Language Classifier service instance2.2.1 Creating the Natural Language Classifier service instance from theBluemix website2.2.2 Creating the Natural Language Classifier service instance using Cloud Foundry commands2.3 What to do next
3.1 Getting started3.1.1 Objectives3.1.2 Prerequisites3.1.3 Expected results3.2 Architecture3.3 Two ways to deploy the application: Step-by-step and quick deploy3.4 Step-by-step implementation3.4.1 Downloading the project from Git3.4.2 Preparing training data3.4.3 Creating and training the classifier3.4.4 Creating the Node.js Express Healthcare Q and A application3.4.5 Deploying the Healthcare Q and A application on Bluemix3.4.6 Testing the application3.5 Quick deployment of application3.6 References
4.1 Getting started4.1.1 Objectives4.1.2 Prerequisites4.1.3 Expected results4.2 Architecture4.3 Two ways to deploy the application: Step-by-step and quick deploy4.4 Step-by-step implementation4.4.1 Downloading the project from Git4.4.2 Reviewing the project structure4.4.3 Creating a Cloudant noSQL DB service instance4.4.4 Preparing training data4.4.5 Creating and training the classifier4.4.6 Querying the trained classifier4.4.7 Evaluating results and updating training data4.4.8 Deploying the application4.4.9 Testing the application4.5 Quick deployment of application4.6 References
5.1 Getting started5.1.1 Objectives5.1.2 Prerequisites5.1.3 Expected results5.2 Architecture5.2.1 Component perspective5.2.2 Role and activity perspective5.3 Two ways to deploy the application: Step-by-step and quick deploy5.4 Step-by-step implementation5.4.1 Creating a Node-RED application5.4.2 Cloning the Git project5.4.3 Preparing training data5.4.4 Creating and training the classifier5.4.5 Querying the trained classifier5.4.6 Evaluating results and updating training data5.5 Quick deployment of application5.6 References
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Content preview from Building Cognitive Applications with IBM Watson Services: Volume 4 Natural Language Classifier

Preface

The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® Watson™ 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 ...

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Building Cognitive Applications with IBM Watson Services: Volume 7 Natural Language Understanding

Sebastian Vergara, Mohamed El-Khouly, Mariam El Tantawi, Shireesh Marla, Lak Sri

Building Cognitive Applications with IBM Watson Services: Volume 5 Language Translator

Valerie Lampkin, Thanh Lam, Muhammad Zain Mustafa, Lak Sri

Building Cognitive Applications with IBM Watson Services: Volume 1 Getting Started

Dr. Alfio Gliozzo, Chris Ackerson, Rajib Bhattacharya, Addison Goering, Albert Jumba, Seung Yeon Kim, Laksh Krishnamurthy, Thanh Lam, Angelo Littera, Iain McIntosh, Srini Murthy, Marcel Ribas

The Internet of Medical Things (IoMT)

R. J. Hemalatha, D. Akila, D. Balaganesh, Anand Paul

Publisher Resources

ISBN: 9780738442594Other