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Book Overview & Buying
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Table Of Contents
Practical C# Projects with .NET
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In this chapter, we covered supervised learning forms of machine learning, which train models around patterns in historical data and use those patterns to predict future values. We talked about how classification is used to predict categorical values while regression predicts numerical values.
Over the course of this chapter, we carried out a complete ML.NET model training experiment using AutoML. This experiment loaded data from a CSV dataset, split the data into smaller training and testing datasets, trained models using different trainers and the training data, and then evaluated those models against the testing dataset using various regression metrics.
Finally, we created a PredictionEngine and used it to generate predicted label values from new rows our trained model had never encountered, and showed how these predictions could potentially drive business decisions.
This concludes Part 3 of this book. In the fourth and final part of the book, we'll leave...