/California-House-Pricing

contains a machine learning project aimed at predicting the median house prices in California based on various features such as the number of rooms, geographical location, and others.

Primary LanguageHTML

California Housing Price Prediction

This project is a machine learning application aimed at predicting the median house prices in California based on various features such as the number of rooms, geographical location, and others. The application uses a trained machine learning model to provide accurate predictions.

Project Structure

├── app.py
├── california_housing_model.pkl
└── templates
    └── home.html

app.py: The main application file that runs the web server and handles user requests.
california_housing_model.pkl: The pre-trained machine learning model used for predicting house prices.
templates/home.html: The HTML template for the home page of the application.

Installation

  1. Clone the repository:

bash

git clone <repository-url>
cd <repository-name>
  1. Install the required packages:

bash

pip install -r requirements.txt
  1. Usage
Run the application:

bash

python app.py

Open your web browser and navigate to http://localhost:5000 to access the application.

Features

Predicts median house prices based on user input for various features.
User-friendly web interface for easy interaction.
Utilizes a trained machine learning model for accurate predictions.