Overview of Microsoft Azure AI Services
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Microsoft Azure provides various cloud services across different categories including: - Computer Vision API and Face API allow analyzing images to extract metadata and identify faces. - Speech and language APIs allow converting speech to text, understanding intent, correcting spelling, and translating between languages. - Knowledge APIs allow exploring relationships between academic papers and providing personalized recommendations. - Search APIs allow integrating intelligent search capabilities for images, news, videos and the web into applications. - Intelligence and analytics services allow embedding machine learning and developing predictive models at scale.
Overview of Microsoft Azure AI Services
- 1. 1 Microsoft Azure Services March 2017 C 2017
- 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 data C 2017
- 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 C 2017
- 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 C 2017
- 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 C 2017