Univariate linear regression with gradient descent

In this subsection, we will implement univariate linear regression for the Boston housing dataset, which we used for exploratory data analysis in the previous chapter. Before we fit the regression line, let's import the necessary libraries and load the dataset as follows:

In [1]: import numpy as np
        import pandas as pd
        from sklearn.cross_validation import train_test_split
        from sklearn.linear_model import LinearRegression
        import matplotlib.pyplot as plt
        %matplotlib inline
In [2]: from sklearn.datasets import load_boston
        dataset = load_boston()
        samples , label, feature_names = dataset.data, dataset.target, dataset.feature_names
In [3]: bostondf = pd.DataFrame(dataset.data)
        bostondf.columns = dataset.feature_names
        bostondf['Target Price'] = dataset.target
...