Hello everyone and welcome to the linear regression project exercise overview lecture.
In this lecture we're going to get a brief overview and background for the project exorcized notebook
concerning the linear regression project.
Let's go ahead and jump to the notebook now.
All right.
Here I am at the notebook as a quick note you can find this linear regression project exorcized notebook
under the machine learning sections linear regression folder.
You'll notice that there's two notebooks here.
Linear Regression Dasch practic project exercise and linear regression Dasch project exercise solutions
.
Go ahead and attempt the exercise before checking out the solutions which will have all the code fill
them and then you'll also notice an e-commerce customers file.
That's going to be the source of our data for this project exercise.
OK let me go ahead and give you some background for this project.
You just got some contract work with an e-commerce company based in New York City that sells clothing
online but the store also has in-store style and clothing advice sessions.
Customers can come into the store have sessions or meetings if a personal stylist and then they can
go home and order either through immobile app or web site for the Kloves they want.
The company is trying to decide whether to focus their efforts on their mobile apps experience or on
their Web site experience.
And they've hired you on contract to help them figure it out and then you can go ahead and get started
by just analyzing the customer data.
And another quick note we're going to be dealing with some artificially generated data.
It has credit card numbers and emails.
But don't worry none of those are real.
You'll go ahead and just follow along that you've done for other exercises of the imports.
Getting the data and just following the instructions written in bold you should keep in mind that you
may want to insert cells if you don't want to overwrite the current output.
Then you'll also do some exploratory data analysis with seaborne creating some of these visualizations
and diagrams trying to understand the data and you'll answer some questions about the data.
Then you will create training and testing sets for your data.
You'll train a model and you'll predict based off of your test data then you'll evaluate your model
and also look at the residuals and you'll have a conclusion.
OK best of luck on the project exercise and coming up next is a walk through solution of all the code
of explanations.
Thanks everyone and I hope you enjoyed the project.