Store your data, predict the futureThe real estate home price data file mentioned below was compiled by Martin from Redfin data for the Rex Manor neighborhood of Mountain View, California.
Speaker: Martin Omander
Level: Intermediate | Room: 3525 | 9:45 AM Saturday
- Make your smart applications smarter with Google's Prediction API. Take advantage of Google's machine learning algorithms to make recommendations, analyze Twitter, detect spam, classify documents, identify languages and more.
- Store your applications' data securely and efficiently in Google's data centers with the Storage API.
If you've ever wanted to buy a house or sell your home, and would like a reasonable estimate for what the ultimate sale price will be in this market, you can get a real estate agent's take, or you can use Google Prediction API (henceforth Prediction) to give you another estimated price, given available market data. The idea is, you grab a number of sale price records for the ZIP code you want to buy or sell in, feed the data into Prediction, and Prediction will spit out a number based on the data you fed it. Besides spitting out scalar values, Prediction also does classification. To get your feet wet, here is a beginner tutorial that figures out, in an automated way, whether some text you pass in is English, French or Spanish:
Assuming you were able to successfully use Google's Prediction API, in conjunction with Google Storage and Google's APIs Explorer Tool, to classify samples of text that you pass in, the next step is to predict a sale price for your home.
- Download Martin's houses.csv data here
- Using the same steps in the tutorial above, upload the houses.csv data into Google Storage, and then use the data to train Prediction
- After training is complete, we want to get a predicted price. To do this, we want to pass in the values for a house that we want to buy or sell. Let's say we're trying to sell a 3 bedroom, 3 bathroom, 1800 square foot, built in 1960, single family residence. I found that when I tried to pass in the following as a value for the csvInstance key, I got an error:
3 3 1800 1960 houseI then tried the same thing with commas, but that didn't work either. What I found finally worked is, in the APIs Explorer tool, when specifying the value of the csvInstance, you need to count how many field values you are putting in, let's call it n (in this case, n equals 5), then provision that same number by clicking on "Add" n times, and manually insert the values in order, like so: