Add Natural Language Processing AI power to App by LUIS API

Integrate Natural Language Processing in App by Microsoft Cognitive Services Language Understanding Intelligent Service

What you'll learn:

• Able to add natural language processing Artificial Intelligence capabilities in application like Chatbot, Web App or IOT App
• Able to build custom LUIS model
• Able to integrate custom LUIS model into Chatbot, Web App or IOT App
• Able to build custom machine learning language model

Why you should enroll for this course?

Artificial Intelligence (AI) is going to be a core component of traditional applications.

Microsoft Cognitive Service APIs like LUIS API enables developers to build custom machine learning language model.

Artificial Intelligence in the form of Cognitive APIs like Language Understanding Intelligent Service (Natural Language Processing -NLP ) enables application to process natural language.

AI powered Chatbot with natural language processing capabilities will dominate traditional web and mobile app.

Microsoft Cognitive Service APIs like LUIS APIis product of Artificial Intelligence, created using Machine Learning specially byActive Learning (Semi-Supervised Learning-SSL).

For details, please watch the video on “Why this course is important to add Artificial Intelligence in application”.

Course Includes:

Briefly introduced:

• Overview of Microsoft Cognitive Services
• Overview of Language Understanding Intelligent Service (LUIS)

LUIS Basic concept:

Every concept of LUIS building block is explained with real-world example and hands on codingsupported byextensive code walk-through

• What is LUIS model, Intent?
• What is entity (simple, pre-built, hierarchical, composite, list)?
• How a list entity helps to increase entity detection?
• What is features in machine learning?
  
• What is phrase list and how phrase list helps to improve LUISperformance?
• How phrase list and list entity differs andwhen to use which one?

Design thecustom LUIS model

Designing of custom LUIS model includes every concept and building block of LUIS with a real world use case.

• Identifying model andIntent.
• Identifying entities.
• Identifying phrase list.
• Identifying utterances and typo/misspelling consideration.

Build the customLUIS model

• Build the LUIS model bycreating LUIS model, intent, entities.
• Adding utterances to intent and labeling the entities.

Followed by

• Trainand Test the LUIS model (interactive testing)
• Create Bing Spell Check API in Azure portal
• Adding Bing Spell Check API to correct typo/misspelling from user query/utterances.
• Create Azure LUIS APIin Azure portal and get endpoint key (with free/paid tier).
• Publishing to HTTP endpoint using this endpoint key
• How LUIS improves its performance using Phrase List andby active learning - review endpoint utterances.
• Build the LUIS model with prebuilt domain model: from model training, testing and publishing to HTTP endpoint; Integrating with IOT App.
• Demonstration: integration of LUIS model withchabot and IOT app —debugging and code walk-through on how LUIS gets natural language from apps and parse query and get back to chatbot and web app.
• Bonus Lecture:Improve LUIS model performance using phrase list and reviewing the endpoint utterances.