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Julia for Data Science by Zacharias Voulgaris PhD

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CHAPTER 11: Supervised Machine Learning

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Supervised machine learning is truly the core of data science, as all of the directly applicable insights stem from the outputs of this part of the process. Its most common types are classification and regression, depending on the nature of the target variable.

It would be quite a feat to do this topic justice, as there are so many different methods that fall under its umbrella. However, we’ll cover the most commonly used ones and demonstrate how they can be implemented in Julia, relying on the following packages: DecisionTree, BackpropNeuralNet, ELM and GLM. Make sure that you have them installed on ...

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