In this notbook we I am going to work on California Housing Prices dataset from the StatLib. This dataset was based on data from the 1990 California census. It is not exactly recent, but it has many qualities for learning, This data has metrics such as the population, median income, median housing price, and so on for each block group in California. My model learns from this data and is able to predict the median housing price in any block, given all the other metrics.
- Numpy
- Pandas
- matplotlib
- seaborn
- sklearn
- missingno
- DecisionTreeRegressor