Programming Exercise 1: Linear Regression
Machine Learning
Introduction
In this exercise, you will implement linear regression and get to see it work
on data. Before starting on this programming exercise, we strongly recom-
mend watching the video lectures and completing the review questions for
the associated topics.
To get started with the exercise, you will need to download the starter
code and unzip its contents to the directory where you wish to complete
the exercise. If needed, use the cd command in Octave to change to this
directory before starting this exercise.
You can also find instructions for installing Octave on the “Octave In-
stallation” page on the course website.
Files included in this exercise
ex1.m - Octave script that will help step you through the exercise
ex1 multi.m - Octave script for the later parts of the exercise
ex1data1.txt - Dataset for linear regression with one variable
ex1data2.txt - Dataset for linear regression with multiple variables
submit.m - Submission script that sends your solutions to our servers
[?] warmUpExercise.m - Simple example function in Octave
[?] plotData.m - Function to display the dataset
[?] computeCost.m - Function to compute the cost of linear regression
[?] gradientDescent.m - Function to run gradient descent
[†] computeCostMulti.m - Cost function for multiple variables
[†] gradientDescentMulti.m - Gradient descent for multiple variables
[†] featureNormalize.m - Function to normalize features
[†] normalEqn.m - Function to compute the normal equations
? indicates files you will need to complete
† indicates extra credit exercises
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