Ex1_Linear_regression_prediction_models

This programming exercise was done as part of Coursera's Machine Learning Course (Stanford University), taught by Prof. Andrew Ng.

Predict profits for a food truck in a city given population data

• Implemented univariate linear regression and predicted profits for a food truck to select a city for expansion of the restaurant chain
• Linear regression parameters were fit to the dataset (containing population and profit data for different cities) using gradient descent

Predict housing price given size of house and number of bedrooms

• Implemented multi variate linear regression to predict prices of houses given the size of the house and number of bedrooms, using a training set of housing prices in Portland, Oregon.
• Normalized features and used gradient descent to fit the parameters
• Experimented with learning rates
• Compared predictions with results from normal equations