Microsoft Azure AI Services Cheat Sheet

1. 1
Microsoft Azure Services
March 2017
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2. 2
Computer Vision API: Distill actionable information from images
Content Moderator: Automatically moderate text, images, and videos, augmented with
human review Emotion API: Personalize experiences with emotion recognition
Face API: Detect, identify, analyze, organize, and tag faces in photos
Video API: Analyze, edit, and process videos within your app
Vision
Speech
Bing Speech API: Convert speech to text and back again, and understand its intent
Custom Speech Service: Fine-tune speech recognition for anyone, anywhere
Speaker Recognition API: Give your app the ability to know who's talking
Language
Bing Spell Check API: Detect and correct spelling mistakes within your app
Language Understanding Intelligent Service: Teach your apps to understand commands
from your users
Linguistic Analysis API: Easily parse complex text with language analysis
Text Analytics API: Detect sentiment, key phrases, topics, and language from your text
Translator API: Translate speech and text with a simple REST API call
Web Language Model API: Leverage the power of language models trained on web-scale
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3. 3
Academic Knowledge API: Explore relationships among academic papers, journals, and
authors
Entity Linking Intelligence Service: Contextually extend knowledge of people, locations,
and events
Knowledge Exploration Service: Add interactive search over structured data to your project
QnA Maker: Distill information into conversational, easy-to-navigate answers.
Recommendations API: Provide personalized product recommendations for your
customers
Knowledge
Search
Bing Autosuggest API: Give your app intelligent autosuggest options for searches
Bing Image Search API: Bring advanced image and metadata search to your app
Bing News Search API: Link your users to robust and timely news searches
Bing Video Search API: Trending videos, detailed metadata, and rich results
Bing Web Search API: Connect powerful search to your apps
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4. 4
HDInsight: A managed Apache
Hadoop, Spark, R, HBase, and Storm
cloud service
Cognitive Services: Embed
intelligence to enable natural and
contextual interactions. Augment
user experience with machine-based
intelligence
Data Lake Analytics: Big Data
analytics. Analyze any kind of type
and size of data
Power BI Embedded: Embedded
interactive visualizations to support
interactive reports and dashboards
Intelligence & Analytics
Machine Learning: Cloud services
that supports development and
deployment of predictive analytics
solutions.
Azure Bot Service: Intelligent,
server-less bot service. Built-in
templates support multiple channels
and scales on-demand
Data Lake Store: Hyper-scale
repository for big data analytics
workloads
Azure Analysis Services: Analytics
engine without need to deploy
infrastructure and supports industry
data visualization tools
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5. 5
Artificial Intelligence, Banking, Big Data,
Business Analytics, Business
Architecture, Business Capability,
Business Intelligence, Business
Leadership Business Process, Business
Transformation, Chat Bots, Chief Data
Architect, Cloud, Customer Centricity,
Customer Relationship Management ,
Data Architecture , Data Assessments,
Data Governance, Data Integration,
Data Process Modeling, Data Quality,
Data Science, Data Strategy,, Data
Visualization, Data Warehouse, Design,
Deep Learning, Financial Services,
Enterprise Architecture, FSLDM,
Hadoop, Information Lifecycle
Management, Investment, Machine
Learning, Master Data Management,
Metadata Management, Mobile, Next
Generation Data Platform, Open Data,
Open Source, Python, R, Reference
Data Management, Roadmap, Risk
Management, Spark, Startup,
Technology Stack, Thought Leadership
Craig C. Milroy
@craigmilroy
ca.linkedin.com/in/craigcmilroy
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