The problem that we are going to solve here is that given a set of features that describe a house in Boston, our machine learning model must predict the house price. To train our machine learning model with boston housing data, we will be using scikit-learn’s boston dataset.
In this dataset, each row describes a boston town or suburb. There are 506 rows and 13 attributes (features) with a target column (price). https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.names
Original file is located at Google colab link