We created and predicted a linear model from Sydney house prices, so we found the 'mse' and 'rmse' results.
200,000 Sydney property sales from 2000-2019 scarped from realestate.com.au
There are some general library requirements for the Project. The general requirements are as follows.
- Numpy
- Pandas
- Scikit-learn
- Statsmodels
For Visualization
- Matplotlib
- Seaborn
- Missingno
Sydney property prices from 2000 to 2019. The following steps were followed in this project:
- Import Module and Data
- Data Analysis
- Creating a Table Describing The Detailed Properties Of The Data
- Data Visualization
- Data Classification
- Get Dummies
- Outlier Data
- Missing Data Filling
- Building a Model
| Project Team |
|---|
| Furkan KARAKUZ |
| Oğuzhan AKKURT |
| Muhammed Nafiz CANITEZ |