## File descriptions
* `train_ames.csv` - the training set
* `test_ames.csv` - the test set
* `sample_submission.csv` - an example of a valid submission

## About Dataset
The Ames Housing Dataset is a well-known dataset in the field of machine learning and data analysis. It contains various features and attributes of residential homes in Ames, Iowa, USA. The dataset is often used for regression tasks, particularly for predicting housing prices.

We will be working with a modified version of this dataset that contains the following variables.

* LotFrontage: Linear feet of street connected to property
* LotArea: Lot size in square feet
* Street: Type of road access
* OverallQual: Overall material and finish quality
* OverallCond: Overall condition rating
* YearBuilt: Original construction date
* YearRemodAdd: Remodel date
* MasVnrArea: Masonry veneer area in square feet
* TotalBsmtSF: Total square feet of basement area
* CentralAir: Central air conditioning
* 1stFlrSF: First Floor square feet
* 2ndFlrSF: Second floor square feet
* LowQualFinSF: Low quality finished square feet (all floors)
* BsmtFullBath: Basement full bathrooms
* BsmtHalfBath: Basement half bathrooms
* FullBath: Full bathrooms above grade
* HalfBath: Half baths above grade
* Bedroom: Number of bedrooms above basement level
* Kitchen: Number of kitchens
* TotRmsAbvGrd: Total rooms above grade (does not include bathrooms)
* Fireplaces: Number of fireplaces
* GarageYrBlt: Year garage was built
* GarageCars: Size of garage in car capacity
* GarageArea: Size of garage in square feet
* WoodDeckSF: Wood deck area in square feet
* OpenPorchSF: Open porch area in square feet
* EnclosedPorch: Enclosed porch area in square feet
* 3SsnPorch: Three season porch area in square feet
* ScreenPorch: Screen porch area in square feet
* PoolArea: Pool area in square feet
* YrSold: Year Sold
* SalePrice - the property's sale price in dollars. This is the target variable that you're trying to predict.