Final Project: predicting the growth & change of Boston real estate market Jessica Hu, Annie Li, Bill Zheng 1: What are we working? This project is specifically oriented to predict the change of Boston’s real estate market in the future by learning this region’s past. We will incorporate machine learning into the process of predicting housing prices. 2: What are the data sources? The data source will come from the real estate resources provided by the state government. 3: what are the training algorithms? For now, we are using generalized linear models such as the least squares to compare the pricing of the houses with different conditions. As time progressed, we will incorporate more and more sophisticated data learning methods to meet our needs. 4: what will the visualization look like? The visualization will take in many forms: bars, lines, charts, etc. They can be customized by the users as they wish. 5: what are our project plans? Week 3: starting the basis of the application: making algorithm tests. Annie: Building the backbone of the program (make sure that the hardware runs properly) Jessica: Programming the algorithm (using all 3 computers) Bill: Test the efficacy of different algorithms, making sure that we use the most efficient algorithm (least amount of memory storage for learning and has the max depth). Week 4: Server development Annie: Importing the data to the server Jessica: Developing the server (hardware-wise) Bill: Building the server environment and making sure that everything works. Week 5: Web development Annie: coding the web interface Jessica: designing the website. Bill: maintaining the website (make sure that the server and the website fits properly) Week 6: Finalizing Application Annie: building the link between app, web, and server Jessica: importing the data between app, web, and server Bill: Programming the application and publishing it. Weeek 7: Web Forms development Annie: load, and train the data model Bill: set up the web page Jessica: D3 visualization (Donutchart, scatterplot) Intention: Make a form which the user can input features, and base on the features we predict the price using the model. Tasks: Connecting lab3, lab4 and lab5. Annie: train the data model Bill: set up the form which the user inputs features on the web page Jessica：make the link between the data model and the inputs