This is the problem statement :
https://www.kaggle.com/camnugent/california-housing-prices/code?datasetId=5227&sortBy=voteCount
Programming Language : python. Models used : Linear Regressor, Gradient Boosting Regressor
During the project , I applied some of the machine learning and data science methods that I had learnt till the point of beginning the project.
I learnt :
- A cool way to visualise things, that is the longitute-latitutde map visualisation.
- Learnt about stratified sampeling
- Learnt the meaning of pipelining but haven't implemented it yet
Note: Pipelning is nothing but doing stuff in one place by puting your methods constructively in formats of classes and functions and implementing it oneshot in the main.
use this link to understand it : https://valohai.com/machine-learning-pipeline/