The Laptop Price Predictor is a Streamlit web application designed to predict the prices of laptops based on various features. It leverages machine learning models trained on laptop data to provide accurate price estimations for different laptop configurations.
The app utilizes a dataset containing information about various laptops, including features such as Company, Type Name, RAM, Weight, HDD, SSD, GPU brand, Touchscreen, IPS, PPI, CPU brand, and operating system.
The app is deployed on Streamlit Cloud and can be accessed here.
- Single Prediction: Users can input the details of a single laptop and get the predicted price.
- Interactive Interface: Simple and user-friendly interface for inputting laptop specifications.
- Real-time Prediction: Instant prediction of laptop prices based on user input.
- Model Evaluation Metrics: Display of model evaluation metrics to assess prediction accuracy.
- Navigate to the app using the provided link.
- Select various features of the laptop from the sidebar, such as Company, Type Name, RAM, Weight, HDD, SSD, GPU brand, Touchscreen, IPS, PPI, CPU brand, and operating system.
- Click on the "Predict" button to generate a predicted price for the specified laptop configuration.
To run the app locally, follow these steps:
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Clone this repository to your local machine:
git clone https://github.com/RobinMillford/laptop-price-predictor.git
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Navigate to the project directory:
cd laptop-price-predictor -
Install the required dependencies:
pip install -r requirements.txt
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Run the Streamlit app:
streamlit run app.py
- Python
- Streamlit
- pandas
- scikit-learn
- joblib
This project is licensed under the AGPL-3.0 license - see the LICENSE file for details.