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Hyf azure ml_1

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HACK YOUR FUTURE
BELGIUM
Inspired by the
official MS Azure
Documentation
Modern Analytics
Guidelines
2021

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Hack
Your
Future
Machine Learning on Azure
Azure Cognitive Services
Computer Vision – Face API
Custom Vision
Text Analytic...

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Domain Specific Pretrained Models
To reduce time to market
Azure
Databricks
Machine
Learning VMs
Popular Frameworks
To bui...

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Hyf azure ml_1

  1. 1. HACK YOUR FUTURE BELGIUM Inspired by the official MS Azure Documentation Modern Analytics Guidelines 2021
  2. 2. Hack Your Future Machine Learning on Azure Azure Cognitive Services Computer Vision – Face API Custom Vision Text Analytics Anomaly Detector – Metrics Advisor
  3. 3. Domain Specific Pretrained Models To reduce time to market Azure Databricks Machine Learning VMs Popular Frameworks To build machine learning and deep learning solutions TensorFlow PyTorch ONNX Azure Machine Learning Language Speech … Decision Vision Productive Services To empower data science and development teams Powerful Hardware To accelerate deep learning Scikit-Learn PyCharm Jupyter Familiar Data Science Tools To simplify model development Visual Studio Code Command line CPU GPU FPGA From the Intelligent Cloud to the Intelligent Edge Azure Cognitive Services
  4. 4. Azure Cognitive Services Language Vision Decision Speech Recognize, identify, caption, index, and moderate your pictures, videos, and digital ink content. Convert spoken audio into text, use voice for verification, or add speaker recognition to your app. Allow your apps to process natural language with pre-built scripts, evaluate sentiment and learn how to recognize what users want. Build apps that surface recommendations for informed and efficient decision-making. Video Indexer Computer Vision Face Custom Vision Form Recognizer Video Indexer Speaker Recognition Speech Translation Speech to Text Text to Speech Language Understanding Immersive Reader Translator QnA Maker Text Analytics Anomaly Detector Content Moderator Personalizer Metrics Advisor
  5. 5. https://azure.microsoft.com/en-in/services/cognitive- services/computer-vision/ http://localhost:8888/notebooks/azure_cv_1.ipynb https://westcentralus.dev.cognitive.microsoft.com/docs/servic es/computer-vision-v3-1- ga/operations/56f91f2e778daf14a499f21b
  6. 6. "surprise": 0.9952837
  7. 7. https://azure.microsoft.com/en-in/services/cognitive- services/face/ http://localhost:8888/notebooks/azure_cv_face_api.ipynb https://westus.dev.cognitive.microsoft.com/docs/services/563 879b61984550e40cbbe8d/operations/563879b61984550f303 95236
  8. 8. to introduce drivers and riders right away three weeks That left us more time to spend optimizing the user experi Face API
  9. 9. “Now, companies are simply pushing sales people into the field and they’re learning through experience— a ridiculously expensive way to train. Every deal lost due to lack of confidence costs the company real money. If we can minimize that and actually get sales people ready to sell, it’ll have a huge impact on productivity,” Jim Ninivaggi Senior Vice President Business Development Problem Training sales people through experience is ridiculously expensive. Every deal lost due to lack of confidence costs the company real money. Solution Create a training platform that allows sales reps to perfect their pitch through video and Cognitive Services. Utilizing Face API, Emotion API, and Text Analytics, we both analyze their pitch, and feed an ML model to provide feedback on their performance. Power your Content. Power your Sales. Brainshark
  10. 10. Custom Vision API – a short explanation… This service is an easy-to-use tool for prototyping, improving, and deploying a custom image classifier to a cloud service, without any background in computer vision or deep learning required. “cat” “dog” Model Custom Vision
  11. 11. Best Practices for using Custom Vision API • Use at least 30 images for each tag • Images should be the focus of the picture • Use sufficiently diverse images and backgrounds. • Train with images that are similar in {quality, resolution, lighting, etc.} to the images that will be used in prod • Current project limitations while in preview: 1000 images, 50 tags, 20 iterations saved • Current account limitations while in preview: 20 projects, 1000 predictions per day
  12. 12. Example Customer Scenarios Customer Support • Enable a customer to identify a product for support by taking a photo. No finding the manual or pulling the appliance out to identify it! Service Engineers • Identify parts for ordering Manufacturing • Fault detection on assembly lines to avoid machine downtime and drop in production rates (provided differences are obvious) Data Scientists • Automatic tagging instead of manual, to create features or labels
  13. 13. https://azure.microsoft.com/en-us/services/cognitive- services/custom-vision-service/ https://www.customvision.ai/projects https://docs.microsoft.com/en-us/azure/cognitive- services/custom-vision-service/
  14. 14. Sentiment analysis positive or negative sentiment Key phrase extraction key phrases Topic detection trending topics Language detection language
  15. 15. https://azure.microsoft.com/en-us/services/cognitive- services/text-analytics/#features http://localhost:8890/notebooks/Downloads/library%20 5/sentiment-sanitized.ipynb https://westus2.dev.cognitive.microsoft.com/docs/servi ces/TextAnalytics-v3-1-preview-3/operations/Sentiment
  16. 16. Recognition of unusual patterns of behavior in data that don’t conform to expected outcomes. What is Anomaly Detection
  17. 17. The Challenges from Real-World Data Manual rule setting won’t scale and adapt AD learns from the data on rules which differentiate outliers from normal pattern automatically AD automatically selects the best pre-built model from model pool behind the scenes AD hides the complexity and provides ONE intuitive parameter to change sensitivity Many types of time series that no single algorithm fits all Many existing solutions require data science knowledge
  18. 18. Anomaly Detector Service Take time series as input Auto model selection and inference Return anomaly related metadata (is Anomaly, range of expected value…) Microsoft Cognitive Services To ensure the health of your business, you want to track your key metrics like revenue and understand whether something is out of historical pattern. Sensor time series data, you want to be alerted on the drifting which could imply system malfunctions. Example: Example:
  19. 19. Metrics Advisor (preview): Metrics Advisor is a part of Azure Cognitive Services that uses AI perform data monitoring and anomaly detection in time series data. The service automates the process of applying models to your data, and provides a set of APIs web- based workspace for data ingestion, anomaly detection, and diagnostics - without needing to know machine learning. Example: Example:
  20. 20. Demos Intelligent Kiosk: http://aka.ms/kioskapp Demo web APP: https://aka.ms/addemo
  21. 21. When Should I Use Anomaly Detector? Real-Time Business Health You have KPIs reflecting business & product health, you want to monitor them 24X7 to avoid business loss Interactive Data Analytics Analyzing metric data to understand whether the data contain anomalies out of historical pattern IoT – Remote Monitoring Monitor status of a system or device and get early warning of potential anomalies
  22. 22. Benefits Easy to setup and configure Automatically ingest all of your data feeds with a single API. Powerful inference engine Intelligently applies multiple anomaly detection approaches Completely self- training No need for lots and lots of labeled training data. Offers customization capabilities Tune sensitivity of anomaly detection based on your needs. Scales to large volumes Ingest large amounts of data without worrying about performance. Works in Cloud and Edge Consume from the Cloud API or deploy on edge devices as container.
  23. 23. Proven Technology within Microsoft • 400+ teams across Azure, Windows, Office, Bing… • Millions of time series • Thousands of active users within Microsoft
  24. 24. Basic SKU(Stock-Keeping-Unit) Case Study: Data cleansing for predictive maintenance • Using aircraft data (potential & available data) to generate predictive maintenance models to: – Increase fleet availability – improve mission & material planning – reduce maintenance burden • Challenges: Equipment interferences Arc in micro-secs Military Data Noisy Data
  25. 25. Azure Stack Solution: Anomaly Detector Basic SKU (Stock-Keeping-Unit) container deployed in Azure Stack to clean noises from arc signals
  26. 26. Anomaly Detector “Innovation has always been a driving force at Airbus. Using Anomaly Detector, an Azure Cognitive Service, we can solve some aircraft predictive maintenance use cases more easily.” Peter Weckesser Digital Transformation Officer Airbus Anomaly Detector video
  27. 27. Situation: Solution: Impact: “Only Microsoft offered the proven, cutting-edge technologies and models that have been trained on Microsoft data sets on a very large scale and are available completely disconnected.... All of this accelerates our time to market, and that has been the key differentiator for us.” Airbus innovates continually, ever mindful of the strict security requirements that constrain many of its customers, like government agencies and international security organizations. It also envisioned AI applications to reimagine answers to complex problems. —Marcel Rummens, Product Owner of Internal AI Platform, Airbus The company created its own restricted cloud with Azure AI solutions, like its aircraft anomaly detector. It used Azure Cognitive Services to create a pilot training chatbot and a predictive maintenance solution based on Anomaly Detector. Airbus uses the built-in functionality of Cognitive Services and Azure AI solutions to hasten development, shortening time to market. The solutions it’s creating have myriad benefits, from optimizing military aircraft maintenance to making pilot training more effective. Customer: Airbus Industry: Defense and Intelligence Size: 10,000+ employees Country: Germany Products and services: Microsoft Azure Microsoft Azure AI Microsoft Azure Anomaly Detector Microsoft Azure Cognitive Services Microsoft Azure Cognitive Speech to Text Microsoft Azure Cognitive Text to Speech Microsoft Azure Kubernetes Service Read full story here
  28. 28. Ethical Considerations Privacy & Security Fairness & Transparency

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