Exploring Machine Learning for .Net Developers
summary
Overview of concrete demos and tooling: builds a text-classification model with ML.NET Model Builder on a Wikipedia Detox 250-line dataset, runs an automated search for the best model for 90 seconds training, then generates C# prediction code (label 1 = negative, 0 = positive). Shows TensorFlow and ONNX integration, how to run .NET for Apache Spark, creating an Azure Face API free tier resource, and spinning up Azure Machine Learning automated-ML with a bank-marketing CSV and compute cluster for deployment.
AI-written summary · about
chapters (10)
- 0:00Intro
- 1:10About Niloshima
- 12:52ML.NET - Offerings
- 15:36ML.NET - Model Builder
- 31:54NET for Apache Spark with Multiple Lanuages
- 33:58Other benefits
- 34:55Azure Cognitive Services
- 37:38Cognitive Services Catalogue
- 42:21Azure ML Offerings
- 43:36Azure ML Capabilities
related talks
46mMachine Learning for .NET Developers
45mML: ML.NET: deep dive into dev AI
59mMachine Learning in .NET (ML.NET)
01h 03mMachine learning for C# developers: Introducing ML
42mStep into Machine Learning .NET
52mML.NET - Machine Learning made for .NET
27mN Ways to Do Machine Learning on .NET
50mA Pragmatic Deep Dive into ML.NET