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The Boston housing dataset is widely used across the ML community for benchmarking regression tasks; you can download the .csv filehere(go to the link & just press ctrl+S/command+S; credits: runnily @ github)
The dataset contains multiple columns, also referred to as features, regarding regarding elements of properties across Boston: from CRIM (crime rates in the town) to NOX (nitric oxide concentration), I’ve put down a brief for the variables here.
Variables in order:
CRIM per capita crime rate by town
ZN proportion of residential land zoned for lots >25,000 sq.ft.
INDUS proportion of non-retail business acres per town
CHAS Charles River dummy variable
NOX nitric oxides concentration (parts per 10 million)
RM average number of rooms per dwelling
AGE proportion of owner-occupied units built prior to 1940
DIS weighted distances to five Boston employment centres
RAD index of accessibility to radial highways
TAX full-value property-tax rate per $10,000
PTRATIO pupil-teacher ratio by town
B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
LSTAT % lower status of the population
MEDV Median value of owner-occupied homes in $1000's
We’ll try to predict MEDV (median value in $1000s) of the house given the other features.
Uploading a dataset to Hazlo is a pretty painless process, just go to your “Datasets” tab → click on the “Upload” button → enter some context about the dataset & press upload, that’s it!
Awesome, now you’ve deployed your dataset & are almost there! Go to your “Projects” page → click on “Deploy” → choose the dataset as boston-housing → choose “medv” (median value of the house) as the target feature → press “Deploy”
Once you’ve pressed “Deploy”, you can see your models training in real-time and your model should be computed in under a minute.
Cool! You’ve trained, deployed & hosted your very own ML model in just minutes. Now you can press “interact” to view more details about your project. In your project, go to the “Forecasts” tab, input some data & get the predicted price of that house.
That’s it, you can now integrate your model in a host of different way: from shareable links to API connections — the possibilities with Hazlo are limitless!
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