Language Studio and Custom Models
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Since Nov 2021 AZ cognitive for language is having a fresh tool – the Language Studio which is now in Preview. The studio offers multiple prebuilt and preconfigured models which allow you to quickly implement, test and deploy tasks like understanding conversational language, extracting information, classifying text or answering questions. But it goes further and offers multiple features to create, train and deploy custom models that model your data and serves your needs best. Language Studio does that by utilizing workflows that let developers build models without the need of ML knowledge and deploy the results as handy APIs.
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Language Studio and Custom Models
- 2. #GlobalAzure
- 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 New in Cognitive Services • Language Studio Services • Advanced and Custom Modeling • Setting up Language Studio • Demo
- 7. #GlobalAzure LUIS.ai Text Analytics QnA Maker Entity Recognition
- 8. #GlobalAzure First to achieve human 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-based tools Features Azure TextAnalytics Resource
- 10. #GlobalAzure Feature Description Studio REST/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 Studio REST/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 to both Container and API Billing Unit Tracking AZ Portal Text Analytics resource Free (5000 text/month) Pay-as-you-Go (Azure Standard) Commitment tiers
- 13. #GlobalAzure
- 15. #GlobalAzure Combines 4 outputs in a single call 1. Named Entity Recognition 2. Relation Extraction 3. Entity Linking of Medical Concepts 4. Assertion Detection
- 16. #GlobalAzure
- 17. #GlobalAzure Extension of classic sentiment analysis (no extra cost) Higher granularity of target and assessment Gain insights from the sentiment Very suitable to call for action
- 19. #GlobalAzure Improved model quality Personally Identifiable Information (PII) Custom NER
- 20. #GlobalAzure multiple operations in a 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
- 24. #GlobalAzure
- 25. #GlobalAzure https://www.microsoft.com/en-us/ai/responsible-ai Do not use; Carefully consider; Avoid
- 27. #GlobalAzure Test Deploy View Performance Train Model Tag Utterances Build Schema Custom model to predict meaning and get information Scenarios
- 28. #GlobalAzure NLP for conversational apps over data Scenarios Workflow
- 29. #GlobalAzure Build AI models to classify text into custom categories Scenarios Workflow
- 30. #GlobalAzure Custom AI model for domain specific entities in text Scenarios Workflow
- 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
- 34. #GlobalAzure