Deploying Machine Learning Models
Now that we’ve explored the various ways of training and evaluating regression and classification models, let’s end our discussion of ML.NET by showing how models can be deployed.
In this chapter, we’ll cover our final type of machine learning task: multi-class classification as we train and evaluate a simple model. We’ll then take that model and export it to a file on disk. Next, we’ll import it into an ASP.NET Web API application and use the model to evaluate incoming requests.
We’ll also close the chapter with discussions on monitoring and maintaining machine learning models via MLOps and discuss additional topics of interest in ML.NET.
Along the way, we’ll cover the following topics:
- Introducing our multi-class classification model
- Exporting ML.NET models
- Hosting ML.NET models in ASP.NET web applications
- Understanding model performance, data drift, and MLOps
- Surveying...
