What is the Natural Language Classifier API? How can it enhance you current app development efforts? Rahul Garg, a Strategy and Offering Manager focused on NLC, walks through this unique API. Also receive specific examples on how to train and call the classifier. Watch the live replays and learn how to build cognitive apps using other Watson APIs during our Building With Watson web series: https://www.ibm.com/smarterplanet/us/en/ibmwatson/building-with-watson-webinar.html

1. Building an App Using the Natural Language
Classifier

2. #BuildingWithWatson
Housekeeping Items
• Webinar slides, live recording and Q&A will be
emailed
• Ask questions at any time during the presentation
- Use chat window on the webinar panel
- We're on Twitter: @IBMWatson #BuildingWithWatson
© 2015 International Business Machines Corporation

3. #BuildingWithWatson
Our Expert: Rahul A. Garg
© 2015 International Business Machines Corporation
Strategy and Offering
Management, Watson
Solutions

4. #BuildingWithWatson
What will be covered today?
• Overview
• Sample Calls
• Parameters
• Q&A
© 2015 International Business Machines Corporation

5. #BuildingWithWatson
Overview
• Watson Natural Language Classifier interprets
and classifies natural language with confidence.
• NLC is tuned and tailored to short text (1000
characters or less) and can be trained to
function in any domain or application.
• Variety of uses such as Q&A
© 2015 International Business Machines Corporation

6. #BuildingWithWatson
Usage Examples
• Tackle common questions
• Classify SMS texts
• Classify tweets
© 2015 International Business Machines Corporation

7. #BuildingWithWatson© 2015 International Business Machines Corporation

8. #BuildingWithWatson
Sample Application: Questions on the NLC
• This application shows how to build a question-and-
answer application
© 2015 International Business Machines Corporation

9. #BuildingWithWatson
Preparing Data
• Train the NLC using data in comma-separated value (CSV) format.
• Rows vs. Columns
- Row: Example record
- Columns: Based on the number of records; contains representative text to
classify and classes that apply to the text
© 2015 International Business Machines Corporation
CSV file with four records. Each record in this sample
includes the text input and one class, which are separated
by a comma.

10. #BuildingWithWatson
Creating and Training Classifier
• $ curl -i -u "<username>":"<password>"
• -F training_data=@<path_to_file>/weather_data_train.csv
• -F training_metadata= "{"language":"en","name”
:"TutorialClassifier"}"
"https://gateway.watsonplatform.net/natural-language-
classifier/api/v1/classifiers"
• Reference
© 2015 International Business Machines Corporation

11. #BuildingWithWatson
Sample Response
• {
• "name": "TutorialClassifier",
• "language": "en",
• "status": "Training",
• "url": "https://gateway.watsonplatform.net/natural-language-
classifier/api/v1/classifiers/10D41B-nlc-1",
• "classifier_id": "10D41B-nlc-1",
• "created": "2015-05-28T18:01:57.393Z",
• "status_description": "The classifier instance is in its training phase, not yet
ready to accept classify requests"
• }
© 2015 International Business Machines Corporation

12. #BuildingWithWatson
Classifying Text
• $ curl -G -u "<username>":"<password>"
"https://gateway.watsonplatform.net/natural-language-
classifier/api/v1/classifiers/<classifier_id>/classify" --data-
urlencode "text=How hot will it be today?"
© 2015 International Business Machines Corporation

13. #BuildingWithWatson
Sample Response
• {
• "classifier_id": "10D41B-nlc-1",
• "url": "https://gateway.watsonplatform.net/natural-language-
classifier/api/v1",
• "text": "How hot will it be today?",
• "top_class": "temperature",
• "classes": [
• { "class_name": "temperature", "confidence": 0.9998201258549781 },
• { "class_name": "conditions", "confidence": 0.00017987414502176904 }
] }
© 2015 International Business Machines Corporation

14. #BuildingWithWatson
Are you ready to get started?
• Watson App Gallery
• Getting Started Docs
• Toolkit for NLC
• API Explorer
• API Reference Guide
© 2015 International Business Machines Corporation

15. #BuildingWithWatson© 2015 International Business Machines Corporation
Q&A

16. #BuildingWithWatson
© 2015 International Business Machines Corporation
What’s next?
• Look out for a follow up email with a link to the on-demand version of the webinar,
presentation slides and Q&A recap
• The series continues bi-weekly on Wednesdays @ 12pm ET / 9am PT
• Wednesday, December 2, 2015
• Optimize Conflicting Decisions with the Tradeoff Analytics API

17. #BuildingWithWatson
© 2015 International Business Machines Corporation
Thank you for attending!
Contact us
Phone: 1-877-253-0308
Email: wdc-dev@bg.vnet.ibm.com
Online: Watson Developer Cloud