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Book Overview & Buying
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Table Of Contents
Practical C# Projects with .NET
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Over the past few chapters, we've explored uses of AI to build interactive applications that integrate external data. Conversational AI is amazing and powerful, but there's more to AI than conversational AI.
In this chapter, we'll discuss the subfield of machine learning and how you can use historical data to predict future values given a trained machine learning model. We'll walk through this process with a hands-on experiment involving a dataset of student mood information and Internet of Things (IoT) device readings.
We'll load this dataset, split it into a training dataset and a testing dataset, then use those datasets to train a series of models using ML.NET and AutoML. Once we have our trained models, we'll explore their strengths and weaknesses using standard regression metrics and then use the best model to generate new predictions about student moods given proposed environmental...