AI of Things
summary
Azure Machine Learning together with ML.NET and AutoML is used to manage the model lifecycle in an Azure workspace—experiment runs, model versioning and Dockerized inference that can deploy to cloud, Kubernetes, or IoT devices. The talk presents a sentiment-analysis example using 40,000 Wikipedia comments where AutoML evaluates 20+ model/parameter combinations to select the best model, and shows bots built with Bot Framework plus LUIS/QnA Maker and Alexa custom endpoints hosted on .NET Core working end-to-end.
AI-written summary · about
chapters (7)
- 0:00Introduction and welcome
- 4:20What is machine learning
- 14:47Azure ML Studio overview
- 24:17ML.NET for developers
- 35:56AutoML in ML.NET
- 45:40AI-powered virtual assistants
- 1:04:26Q&A and closing
related talks
01h 01mAI and ML imbedded in Azure Data Platform
57mTaking Models to the Next Level with Azure Machine Learning
41mAI + Machine Learning for .NET Developers
51mTaking Models to the Next Level with Azure Machine Learning
01h 00m5 Levels of AI in Microsoft Azure
31mAzure AI Innovations at Microsoft
50mAzure AI, Power new possibilities for every organization
48mBuilding and using AI models responsibly