Posted on 2019-04-29, by fubber.
mp4 | AVC: 1280x720 G_P| Audio:AAC LC 192 Kbps | Total files:80 | mp4, txt, html | 444 MB
Genre: eLearning | Language: English
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
Expand all 78 lectures03:25:25
+Setting Up Environment
+Overview on Cognitive Services
+Overview on Language Understanding Intelligent Service (LUIS)
+LUIS Basic Concept
+Design Custom LUIS Model
+Build Custom LUIS Model
+LUIS Model : Train and Test
+Managing LUIS Keys
+LUIS Model: Publish
4 more sections
Experience as a C# .NET developer
Create a chatbot using Bot Builder SDK (Basic Level)
Visual Studio 2015/2017 Community Edition
Bot Framework Emulator
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 API is product of Artificial Intelligence, created using Machine Learning specially by Active Learning (Semi-Supervised Learning - SSL).
For details, please watch the video on �Why this course is important to add Artificial Intelligence in application�.
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 coding supported by extensive 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 LUIS performance?
How phrase list and list entity differs and when to use which one?
Design the custom LUIS model
Designing of custom LUIS model includes every concept and building block of LUIS with a real world use case.
Identifying model and Intent.
Identifying phrase list.
Identifying utterances and typo/misspelling consideration.
Build the custom LUIS model
Build the LUIS model by creating LUIS model, intent, entities.
Adding utterances to intent and labeling the entities.
Train and 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 API in 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 and by 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 with chabot 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.
Who this course is for:
Developer/Decision maker wants to integrate natural language processing AI capabilities in Chatbot or IOT app Microsoft Cognitive Services LUIS API
C# and .NET Developers passionate about new technology and wants to up skill by learning/implementing Microsoft Cognitive Services LUIS API
College students who passionate to explore and shape their career in Artificial Intelligence, Machine Learning and Natural Language Processing
Developer/Decision maker who wants to create custom machine learning model without help of data scientist.
Width: 1280 pixels
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Duration: 13min 48s
Bit rate: 244 Kbps
Frame rate: 30.000 fps
Aspect ratio: 16:9
Bit depth: 8 bits
Color space: YUV
Audio track: 1
Codec: AAC LC
Bit rate: 192 Kbps N/A
Sampling rate: 48 Khz
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- Ebooks list page : 40360
- 2012-01-02Language, Vision, and Music: Selected Papers from the 8th International Workshop on the Cognitive Science of Natural Language Processing, Galway, Ireland 1999 - International Workshop On The Cognitive Science Of Natural Language Press
- 2019-06-17Natural Language Processing for Social Media
- 2019-06-16Getting Started with Natural Language Processing with Python - Removed
- 2019-06-07Artificial Intelligence and Data Science Series Natural Language Processing Test Your Knowledge
- 2019-06-06Getting Started with Natural Language Processing with Python - Removed
- 2019-06-04Coursera - Natural Language Processing (Columbia University)
- 2019-05-21Coursera - Natural Language Processing
- 2019-05-17Coursera - Natural Language Processing
- 2019-05-06Natural Language Processing and Computational Linguistics Speech, Morphology and Syntax
- 2019-05-01Natural Language Processing and Computational Linguistics Speech, Morphology and Syntax
- 2019-04-29Natural Language Processing with Deep Learning in Python (Updated)
- 2019-04-29NLP - Natural Language Processing with Python
- 2019-04-14Udemy - Data Science: Natural Language Processing (NLP) in Python
- 2019-04-09Natural Language Processing with Deep Learning in Python (Updated)
- 2019-04-09NLP - Natural Language Processing with Python
- 2019-04-07Udacity Natural Language Processing Nanodegree Nd892 V1 0 0
- 2019-04-02Natural Language Processing with Deep Learning in Python (Updated)
- 2019-04-02NLP - Natural Language Processing with Python
- 2019-03-31Natural Language Processing with Deep Learning in Python (Updated)
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