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Learning Microsoft Cognitive Services.
Create intelligent apps with vision, speech, language, and knowledge capabilities using Microsoft Cognitive Services About This Book Explore the capabilities of all 21 APIs released as part of the Cognitive Services platform Build intelligent apps that combine the power of computer vision, speech re...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Packt Publishing,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover
- Copyright
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- Customer Feedback
- Table of Contents
- Preface
- Chapter 1: Getting Started with Microsoft Cognitive Services
- Cognitive Services in action for fun and life changing purposes
- Setting up boilerplate code
- Detecting faces with the Face API
- Overview of what we are dealing with
- Vision
- Computer Vision
- Emotion
- Face
- Video
- Speech
- Bing Speech
- Speaker Recognition
- Custom Recognition
- Language
- Bing Spell Check
- Language Understanding Intelligent Service (LUIS)
- Linguistic Analysis
- Text Analysis
- Web Language Model
- Knowledge
- Academic
- Entity Linking
- Knowledge Exploration
- Recommendations
- Search
- Bing Web Search
- Bing Image Search
- Bing Video Search
- Bing News Search
- Bing Autosuggest
- Getting feedback on detected faces
- Summary
- Chapter 2: Analyzing Images to Recognize a Face
- Learning what an image is about using Computer Vision API
- Setting up a chapter example project
- Generic image analysis
- Recognizing celebrities using domain models
- Utilizing Optical Character Recognition
- Generating image thumbnails
- Diving deep into the Face API
- Retrieving more information from the detected faces
- Deciding whether two faces belong to the same person
- Finding similar faces
- Grouping similar faces
- Adding identification to our Smart-House application
- Creating our Smart-House application
- Adding people to be identified
- Identifying a person
- Summary
- Chapter 3: Analyzing Videos
- Knowing your mood using the Emotion API
- Getting images from a web camera
- Letting the smart-house know your mood
- Diving into the Video API
- Video operations as common code
- Getting operation results
- Wiring up execution in the ViewModel.
- Detecting and tracking faces in videos
- Detecting motion
- Stabilizing shaky videos
- Generating video thumbnails
- Analyzing emotions in videos
- Summary
- Chapter 4: Letting Applications Understand Commands
- Creating language-understanding models
- Register an account and get a license key
- Creating an application
- Recognizing key data using entities
- Understanding what the user wants using intents
- Simplifying development using pre-built models
- Pre-built applications
- Training a model
- Training and publishing the model
- Connecting to the smart-house application
- Model improvement through active usage
- Visualizing performance
- Resolving performance problems
- Adding model features
- Adding labeled utterances
- Looking for incorrect utterance labels
- Changing the schema
- Active learning
- Executing operations based on commands
- Maintaining conversations from unclear utterances
- Completing actions from intents
- Action fulfillment
- Summary
- Chapter 5: Speak with Your Application
- Converting text to audio and vice versa
- Speaking to the application
- Letting the application speak back
- Audio output format
- Error codes
- Supported languages
- Utilizing LUIS based on spoken commands
- Knowing who is speaking
- Adding speaker profiles
- Enrolling a profile
- Identifying the speaker
- Verifying a person through speech
- Customizing speech recognition
- Creating a custom acoustic model
- Creating a custom language model
- Deploying the application
- Summary
- Chapter 6: Understanding Text
- Setting up a common core
- New project
- Web requests
- Data contracts
- Correcting spelling errors
- Natural Language Processing using the Web Language Model
- Breaking a word into several
- Generating the next word in a sequence of words.
- Learning if a word is likely to follow a sequence of words
- Learning if certain words is likely to appear together
- Extracting information through textual analysis
- Detecting language
- Extracting key phrases from text
- Learning if a text is positive or negative
- Exploring text using linguistic analysis
- Introduction to linguistic analysis
- Analyzing text from a linguistic viewpoint
- Summary
- Chapter 7: Extending Knowledge Based on Context
- Linking entities based on context
- Providing personalized recommendations
- Creating a model
- Importing catalog data
- Importing usage data
- Building a model
- Consuming recommendations
- Recommending items based on prior activities
- Summary
- Chapter 8: Querying Structured Data in a Natural Way
- Tapping into academic content using the Academic API
- Setting up an example project
- Interpreting natural language queries
- Finding academic entities from query expressions
- Calculating the distribution of attributes from academic entities
- Entity attributes
- Creating the backend using the Knowledge Exploration Service
- Defining attributes
- Adding data
- Building the index
- Understanding natural language
- Local hosting and testing
- Going for scale
- Hooking into Microsoft Azure
- Deploying the service
- Answering FAQs using QnA Maker
- Creating a knowledge base from frequently asked questions
- Training the model
- Publishing the model
- Improving the model
- Summary
- Chapter 9: Adding Specialized Searches
- Searching the Web from the Smart-House application
- Preparing the application for web searches
- Searching the Web
- Getting the news
- News from queries
- News from categories
- Trending news
- Searching for images and videos
- Using a common user interface
- Searching for images
- Searching for videos.
- Helping the user with auto suggestions
- Adding Autosuggest to the user interface
- Suggesting queries
- Search commonalities
- Languages
- Pagination
- Filters
- Safe search
- Freshness
- Errors
- Summary
- Chapter 10: Connecting the Pieces
- Connecting the pieces
- Creating an intent
- Updating the code
- Executing actions from intents
- Searching news on command
- Describing news images
- Real-life applications using Microsoft Cognitive Services
- Uber
- DutchCrafters
- CelebsLike.me
- Pivothead
- wearable glasses
- Zero Keyboard
- The common theme
- Where to go from here
- Summary
- Appendix A: LUIS Entities and Intents
- LUIS pre-built intents
- LUIS pre-built entities
- Appendix B: Additional Information on Linguistic Analysis
- Part-of-Speech Tags
- Phrase types
- Appendix C: License Information
- Video Frame Analyzer
- OpenCvSharp3
- Newtonsoft. Json
- NAudio
- Definitions
- Grant of Rights
- Conditions and Limitations
- Index.