From the course: Exploring Data Science with .NET using Polyglot Notebooks & ML.NET

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Intro to machine learning, ML.NET, and AutoML

Intro to machine learning, ML.NET, and AutoML

From the course: Exploring Data Science with .NET using Polyglot Notebooks & ML.NET

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Intro to machine learning, ML.NET, and AutoML

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- [Instructor] Now that we've established using Polyglot Notebooks for data analysis and visualization tasks, let's shift gears a bit and talk about machine learning. When working with supervised learning experiments in machine learning, you typically take a large training dataset and use it to train a machine learning model to predict a specific column or label from the dataset based on all the other columns, which we call features. This process takes some time and produces a trained model, but this trained model can take in new features it's never seen before, and quickly predict the associated label that would be associated with those features. For example, you could train a weather model using various weather conditions as features and have the expected amount of rain be the label that you're predicting. In this course, we'll be talking about ML.NET, the primary machine learning library for .NET. ML.NET is powerful, fast, open source, and has been publicly available since 2019…

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