Conclusion
Explore a comprehensive summary of key ML.NET concepts covered in this course. Understand the fundamentals of machine learning, the use of ML.NET CLI, and application structure. Review various supervised and unsupervised learning tasks, deep learning basics, AutoML, and model management techniques. This lesson helps you consolidate your knowledge to confidently apply ML.NET for building and training machine learning models.
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Summary
In this course, we learned how to use ML.NET to build and train ML models. We've covered the main fundamentals of using both the CLI version of the tool and its .NET NuGet libraries. Let’s summarize the concepts we learned in this course.
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Fundamentals of ML: These included the ML terminology, ML process, and the types of ML.
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ML.NET CLI tool: We covered the basic CLI syntax for all available ML task types.
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ML.NET ...
