t70256242/Lagos-Rent-Estimator

Machine Learning model to predict House rent in Various location in Lagos, Nigeria. # Lagos Rent Estimator App ## Overview This is a Flask-based web application that predicts house rental prices in Lagos based on user inputs such as property type, number of bedrooms, number of bathrooms, and location. The app utilizes a trained machine learning model to generate price predictions and provides an interactive user interface built with Flask-WTF and Bootstrap. ## Features - Predicts house rental prices based on user inputs. - User-friendly web interface using Flask and Bootstrap. - Secure contact form with email functionality. - Dynamic dropdowns for property types and locations. - Real-time mean price display for reference. ## Technologies Used - Python (Flask, Flask-WTF, Flask-Bootstrap) - Machine Learning (scikit-learn, DecisionTreeRegressor) - Data Handling (Pandas, NumPy, Joblib) - Frontend (HTML, CSS, Bootstrap) - SMTP for email functionality ## Installation ### Prerequisites Ensure you have the following installed: - Python 3.x - pip (Python package manager) ### Steps 1. Clone the repository: ```sh git clone cd ``` 2. Create a virtual environment (optional but recommended): ```sh python -m venv venv source venv/bin/activate # On macOS/Linux venv\Scripts\activate # On Windows ``` 3. Install dependencies: ```sh pip install -r requirements.txt ``` 4. Set up environment variables: Create a `.env` file in the root directory and add: ```env SECRET_KEY= MY_EMAIL= MY_PASSWORD= ``` 5. Run the application: ```sh python app.py ``` 6. Open a browser and navigate to `127.0.0.1` ## File Structure ``` |-- static/ |-- templates/ |-- app.py |-- load_artifacts.py |-- requirements.txt |-- .env ``` ## Usage ### Predicting House Prices 1. Select property type, location, number of bedrooms, and bathrooms. 2. Click `Submit` to get a price prediction. ### Contact Form 1. Enter your name, email, subject, and message. 2. Click `Send` to submit the form. ## Model Training The model is a `DecisionTreeRegressor`, trained using housing rental da …