This data science project series walks through step by step process of how to build a real estate price prediction. We will first build a model using sklearn and linear regression using banglore home prices dataset from kaggle.com.During model building we will cover almost all data science concepts such as data load and cleaning, outlier detection and removal, feature engineering, dimensionality reduction, gridsearchcv for hyperparameter tunning, k fold cross validation etc. Technology and tools wise this project covers,
- Python
- Numpy and Pandas for data cleaning
- Matplotlib for data visualization
- Sklearn for model building
- Jupyter notebook, visual studio code and pycharm as IDE