Surveying additional ML.NET capabilities
In this book, we covered using ML.NET for regression, binary classification, and multi-class classification. We also covered using AutoML to perform end-to-end experiments for us or perform hyperparameter tuning on our behalf.
ML.NET supports many different tasks, including the following:
- Anomaly detection
- Ranking choices
- Recommending choices based on prior choices
- Time series forecasting
- Image classification and object detection with deep learning
- Text classification with deep learning
- Sentence similarity scores
- Probability analysis
- String tokenization
If you want a more comprehensive list with the latest examples, I recommend you take a look at https://packt.link/1fjPR for a full list of currently supported ML.NET tasks.
Additionally, ML.NET includes an increasing number of built-in transformation, conversion, and scaling operations through its various catalogs attached to the MLContext...
