This is my first Machine Learning model using python for predicting house prices.
While working on this projects I explored various things in machine learning like:
- how to do comprehensive analysis of a problem involving data collection,
- importing it into a Jupyter notebook,
- identifying valuable attributes,
- exploring correlations,
- visualizing data through graphs,
- building a pipeline,
- addressing missing values, and more.
I actively used concepts like cross-validation, train-test splitting, stratified shuffle split, and sampling throughout the project. By employing these techniques, I hoped to improve my understanding of how they can be implemented successfully in real world projects.