(This project is for Udacity students who are enrolled in a full Udacity course experience.)
Note: These instructions apply to Udacity students enrolled in the Full Course Experience. They do not apply to Georgia Tech OMSCS students.
You are the best real estate agent in Boston because you use Machine Learning to predict house prices. One of your clients wants to sell a house and they want you to give them an estimate of the best selling price. You are the Kelley Blue Book of homes, so you want to predict the correct price. Not only that, you should be able to convince your client that your estimate is reasonable.
We have seen a lot of models (DT, NN and so on) and various algorithms (ID3, Gradient Descent, etc.) to learn them in the video lessons. Often when a dataset is given, we are trying to fit it to the best model; that is, the best model that generalizes for data we haven’t seen yet. An important skill of a data scientist is to identify the best model. This project is going to help you analyze a dataset and teach you how to choose the best model that generalizes that dataset.
If you were a carpenter, the project is comparable to you building a desk or a tree house. A carpenter does not build the tools that are required for the construction, but he knows which tools to use to get the job done. Similarly, it is important for a good data scientist to know which tools to use to find the best model.
In this project you will get a chance to work with these "tools" and find a model that gives you the best generalization. From this you will have to estimate the price of a particular house for your client and justify it.
The following sections will help you understand the logistics of the final project: implementation details and submission guidelines. These documents are intended for students with a Udacity Coach who enrolled in the full course experience. If you are previewing the courseware you are welcome to look at these documents as well (but understand that you will not submit your project to Udacity).
If you have any questions about the project, don't hesitate to talk to your coach. Good luck!