In this notebook, I implement a Machine Learning Pipeline to extract, pre-process and transform data on houses in San-Francisco before implementing 3 different ML agorithms on them.
- Linear Regression
- Random Forests
- Decision Trees
By using cross validation, we discover that the Random Forests algorithm performs best for this dataset