Welcome to Machine Learning Housing Corp! This project involves predicting median house values in Californian districts using various machine learning techniques.
The objective of this project is to build a predictive model that estimates median house prices in California based on multiple features of the districts. The dataset contains important variables such as:
- Average number of rooms
- Population density
- Average income
- Proximity to amenities
- A dataset containing house values and relevant features.
- Implementations of various machine learning algorithms (e.g., Linear Regression, Random Forest).
- Data preprocessing steps integrated into the analysis.
- Visualization of results for better understanding.