In this chapter, we will consider the problem of trying to predict the value of houses in Boston's suburbs based on a number of variables, such as the number of rooms and house age. The details of the dataset can be found here: https://www.kaggle.com/c/boston-housing/. This problem is different to the one we considered in the last chapter, as the variable we're trying to predict (price in dollars) is continuous. Models that are able to predict continuous quantities are called regressors, or regression algorithms. There are many such algorithms, but in this chapter, we will focus on the simplest (but very popular) kind, linear regressors.
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