Deploying machine learning models
Resources for Chapter 10 of Data Science in .NET with Polyglot Notebooks
Chapter 10 of Data Science in .NET with Polyglot Notebooks is the last chapter in part 2 of the book and focuses on taking a multi-class classification model, saving it to disk, and loading it into an ASP.NET web API using Microsoft’s PredictionEngine and PredictionEnginePool classes. This chapter also discusses MLOps and ongoing model maintenance and its importance.
Learn data science using ML.NET, OpenAI, and Semantic Kernel
Data Science in .NET with Polyglot Notebooks teaches experienced .NET devs the fundamentals of data science, machine learning, and AI orchestration. It covers topics like ML.NET, OpenAI, Semantic Kernel, career development, and more.
Buy Data Science in .NET with Polyglot Notebooks on Amazon or through Packt in print and digital formats.
Additional Resources
These resources and notes are likely to be helpful while reading Chapter 10 of Data Science in .NET with Polyglot Notebooks.
- ML.NET Documentation
- ML.NET Metrics
- Builtwith.com Metrics on ASP.NET
- Creating an ASP.NET web application in Visual Studio
- Hosting ML.NET models in ASP.NET applications
- ML.NET Workflows
- Save and load trained models
- Introduction to machine learning operations (MLOps) learning path
- Open Neural Network Exchange (ONNX)
- Using an ONNX model in ML.NET
- Analyze review sentiment using a TensorFlow model in ML.NET
- Image classification in ML.NET with TensorFlow
