House Price Prediction using Machine Learning
So to deal with this kind of issues Today we will be preparing a MACHINE LEARNING Based model, trained on the House Price Prediction Dataset.
You can download the dataset from this link.
The dataset contains 13 features :
| 1 | Id | To count the records. |
|---|---|---|
| 2 | MSSubClass | Identifies the type of dwelling involved in the sale. |
| 3 | MSZoning | Identifies the general zoning classification of the sale. |
| 4 | LotArea | Lot size in square feet. |
| 5 | LotConfig | Configuration of the lot |
| 6 | BldgType | Type of dwelling |
| 7 | OverallCond | Rates the overall condition of the house |
| 8 | YearBuilt | Original construction year |
| 9 | YearRemodAdd | Remodel date (same as construction date if no remodeling or additions). |
| 10 | Exterior1st | Exterior covering on house |
| 11 | BsmtFinSF2 | Type 2 finished square feet. |
| 12 | TotalBsmtSF | Total square feet of basement area |
| 13 | SalePrice | To be predicted |
House Price Prediction using Machine Learning in Python
We all have experienced a time when we have to look up for a new house to buy. But then the journey begins with a lot of frauds, negotiating deals, researching the local areas and so on.
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