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049 RIDW
050 4 T55.4-60.8
082 04 006.3|223
090 T55.4-60.8
100 1 Larsen, Leif.
245 10 Learning Microsoft Cognitive Services.
264 1 [Place of publication not identified] :|bPackt Publishing,
|c2017.
300 1 online resource
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
347 text file|2rdaft
505 0 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.
505 8 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.
505 8 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.
505 8 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.
520 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 recognition, and language processing Give your apps
human-like cognitive intelligence with this hands-on guide
Who This Book Is For .NET developers who want to add AI
capabilities to their applications will find this book
useful. No knowledge of machine learning or AI is expected
to follow this book. What You Will Learn Identify a person
through visual inspection and audio Reduce user effort by
utilizing AI-like capabilities Understand how to analyze
images and text in different manners Find out how to
analyze images using Vision APIs Add video analysis to
applications using Vision APIs Utilize Search to find
anything you want Analyze text to extract information and
explore the structure of the text In Detail Microsoft has
revamped its Project Oxford to launch the all new
Cognitive Services platform--a set of 21 APIs to add
speech, vision, language, and knowledge capabilities to
apps. This book will introduce you to all 21 APIs released
as part of Cognitive Services platform and show you how to
leverage their capabilities. More importantly, you'll see
how the power of these APIs can be combined to build real-
world apps that have cognitive capabilities. The book is
split into three sections: computer vision, speech
recognition and language processing, and knowledge and
search. You will be taken through the vision APIs at first
as this is very visual, and not too complex. The next part
revolves around speech and language, which are somewhat
connected. The last part is about adding real-world
intelligence to apps by connecting them to Knowledge and
Search APIs. By the end of this book, you will be in a
position to understand what Microsoft Cognitive Service
can offer and how to use the different APIs. Style and
approach This book adopts a step-by-step approach,
covering the different APIs with a combination of theory
and examples. Downloading the example code for this book.
You can download the example code files for all Packt
books you have purchased from your account at http://
www.PacktPub.com. If you purchased this book elsewhere,
you can visit http://www.PacktPub.com/support and register
to have the code file.
588 0 Print version record.
590 eBooks on EBSCOhost|bEBSCO eBook Subscription Academic
Collection - North America
630 00 Natural language processing.|0https://id.loc.gov/
authorities/names/n91086627
655 4 Electronic books.
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856 42 |3Instructions for reading/downloading the EBSCO version
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901 MARCIVE 20231220
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