Data Science, Linear Regression, Machine Learning, Python, Numpy.
iterations to 1000. We’ll also initialize the coefficients to random values using NumPy’s random module. Step 2: Prepare the data The next step is to prepare the data by loading it into NumPy arrays and splitting it into training and test sets. We’ll also add a column of ones to the training data