Download as PDF, PPTX
Uploaded byIvo Andreev
Language Studio and Custom Models
The document outlines features and functionalities of Azure Cognitive Services focused on language processing, including tools for text analytics, sentiment analysis, entity recognition, and custom AI model creation. It highlights various capabilities like named entity recognition, sentiment analysis, and text summarization, as well as pricing and service limitations. Additionally, it provides links to resources for setting up and utilizing these language services effectively.
More Related Content
Similar to Language Studio and Custom Models
![[Machine Learning 15minutes! Broadcast #67] Azure AI - Build 2022 Updates and...](https://cdn.slidesharecdn.com/ss_thumbnails/20220625ml15minazureaibuild2022updates-220626102255-c87d66ae-thumbnail.jpg?width=640&height=640&fit=bounds)
Language Studio and Custom Models
- 1.
- 2.
- 3.
- 4. #GlobalAzure • Software Architect@ o 20+ years professional experience • Microsoft Azure MVP • External Expert Eurostars-Eureka, Horizon Europe • External Expert InnoFund Denmark, RIF Cyprus • Business Interests o Web Development, SOA, Integration o IoT, Machine Learning, Computer Intelligence o Security & Performance Optimization • Contact ivelin.andreev@icb.bg www.linkedin.com/in/ivelin www.slideshare.net/ivoandreev
- 5. #GlobalAzure • What’s Newin Cognitive Services • Language Studio Services • Advanced and Custom Modeling • Setting up Language Studio • Demo
- 6.
- 7.
- 8. #GlobalAzure First to achievehuman parity Globally available in multiple languages Deployment Options Common Scenarios https://docs.microsoft.com/en-us/connectors/cognitiveservicestextanalytics/
- 9. #GlobalAzure https://language.cognitive.azure.com/home Set of UI-basedtools Features Azure TextAnalytics Resource
- 10. #GlobalAzure Feature Description StudioREST/SDK Docker Named Entity Recognition (NER) Identifies entities in text across several pre-defined categories Custom NER AI model to extract custom entity categories, using unstructured text Language detection Evaluates text, and determines the language it was written Entity Linking Disambiguates the identity of an entity found in text and provides links on Wikipedia Personally Identifiable Information (PII) Identifies entities in text across several pre-defined categories of sensitive information Text analytics for health Extracts information from unstructured medical texts, such as clinical notes and doctor's notes. Sentiment analysis & Opinion mining Sentiment labels (negative, neutral, positive) on granular level for the attributes of a product or service
- 11. #GlobalAzure Feature Description StudioREST/SDK Docker Key phrase extraction Evaluates unstructured text for list of key phrases and main points Text summarization Feature extracts key sentences that collectively convey the essence of a document. Generate summary. Custom text classification Build an AI model to classify unstructured text into custom classes that you define Conversational lang. understanding AI model to bring the ability to understand natural language into apps, bots, and IoT devices Question answering Provides answers to questions extracted from text input, using semi-structured content such as: FAQs, manuals, and documents Orchestration workflow Train language models to connect to multiple services: question answering, conversational language understanding, and LUIS
- 12. #GlobalAzure Prices apply toboth Container and API Billing Unit Tracking AZ Portal Text Analytics resource Free (5000 text/month) Pay-as-you-Go (Azure Standard) Commitment tiers
- 13.
- 14.
- 15. #GlobalAzure Combines 4 outputsin a single call 1. Named Entity Recognition 2. Relation Extraction 3. Entity Linking of Medical Concepts 4. Assertion Detection
- 16.
- 17. #GlobalAzure Extension of classicsentiment analysis (no extra cost) Higher granularity of target and assessment Gain insights from the sentiment Very suitable to call for action
- 18.
- 19. #GlobalAzure Improved model quality PersonallyIdentifiable Information (PII) Custom NER
- 20. #GlobalAzure multiple operations ina single request Same AI model Up to 125K characters throughput, not latency partial feature support
- 21. #GlobalAzure Feature Limitation Preconfigured Features• Max request size: 1MB • Max 25 docs (Async API), 25 (Text summarization) 10 docs (Sentiment, Key Phrase, Opinion), 5 docs (NER, PII) • S Tier-1000 req/sec, S0-Tier 100 req/sec per feature Custom Text Classification • .txt only, no empty files • West US 2, West Europe regions • 20 req/minute, Max request size 125’000 chars • Min 10, Recommended 50 tagged instances per class • Min 10 files, Max 1’000’000 files, Max 10 models per project Custom NER • (Same as Custom Text) • Max file size is 128’000 chars • Min 10 files, max 100’000 files, Max 50 models per project Conversational Language Understanding • 15’000 utterances (500 chars), 500 intents, 100 entities • 60 req/min • Max 100’000 req/month QnA • File types: .tsv (10MB), .pdf (25MB), .txt (10MB), .docx (10MB), .xlsx (3MB) • Max question 1’000 chars, Max answer 25’000 chars • Max QnAs per call: 1000
- 22.
- 23.
- 24.
- 25. #GlobalAzure https://www.microsoft.com/en-us/ai/responsible-ai Do not use;Carefully consider; Avoid
- 26.
- 27. #GlobalAzure Test Deploy View Performance Train Model Tag Utterances Build Schema Custom model topredict meaning and get information Scenarios
- 28. #GlobalAzure NLP for conversationalapps over data Scenarios Workflow
- 29. #GlobalAzure Build AI modelsto classify text into custom categories Scenarios Workflow
- 30. #GlobalAzure Custom AI modelfor domain specific entities in text Scenarios Workflow
- 31.
- 32. #GlobalAzure 5-step Learning Tutorial(from 4000+ guides) • https://docs.microsoft.com/en-us/learn/paths/explore-natural-language-processing/ Language Studio Setup https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/language-studio Try it out https://language.cognitive.azure.com/tryout/sentiment https://language.cognitive.azure.com/tryout/healthAnalysis https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/custom- classification/quickstart?pivots=language-studio Form Recognizer (Preview) • https://formrecognizer.appliedai.azure.com/studio • https://docs.microsoft.com/azure/applied-ai-services/form-recognizer
- 33.
- 34.