The objective of this part of the project is to develop a linear regression model for the given dataset using Gradient Descent methods. The regression model should be built using numpy, pandas, and sklearn. Problem Description: The problem statement :Karl Pearson conducted a survey around 1903 on the height of heights of fathers and their sons. The number of data points in the survey are 1078 samples. It is interesting to see whether son’s height can be predicted given father’s height. Train the linear regression model using each of the following methods: 1) Stochastic Gradient Descent 2) Gradient Descent 3) Mini-batch Gradient Descent
