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Supervised learning involves training a model on labeled data from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
Supervised learning is a type of machine learning where we have a specific outcome we want to predict or classify. In this setting, we first need to have labeled data, which means that we know the correct answer for each example in our dataset. This labeled data is used to train a model, which is essentially a function that maps input data to the correct output. The goal is for the model to learn how to make predictions or classifications on new, unseen data based on the patterns it has learned from the labeled data. The process of training a model on labeled data involves feeding the model examples from the dataset and adjusting its internal parameters to minimize the difference between its predictions and the true labels. This is typically done using an optimization...
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