Laptop Price Prediction in Machine Learning

Laptop Price Prediction

The Laptop Price Prediction is a smart web app that uses machine learning to guess the price of a laptop based on its specifications. It’s a great tool for online shoppers, students, or anyone curious about laptop pricing.

Project Overview

This app takes details like RAM, processor type, storage, and screen size as input and predicts the laptop’s price using a trained regression model. Built with Python and Streamlit, the interface is clean, interactive, and easy to use. The project includes a ready-to-use dataset and a pre-trained model for accurate predictions

Technical Details

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Available Features

• Predict laptop price based on:
  • Company
  • Type
  • Screen Size
  • Screen Resolution
  • CPU
  • RAM
  • Storage
  • GPU
  • Operating System
• Pre-trained ML models using:
  • Random Forest
  • Voting Regressor (Random Forest + Gradient Boosting)
• Performance metrics:
  • R² Score
  • Mean Absolute Error (MAE)
• Currency conversion from INR to USD with customizable exchange rate
• Clean UI using Streamlit
• Includes dataset (laptop_data.csv) and serialized pipeline (pipe.pkl, df.pkl)

Running the Application

1. Install required dependencies: pip install -r requirements.txt
2. Launch the Streamlit application: streamlit run app.py

Machine Learning Models Implemented

• Multiple Linear Regression
• Ridge Regression
• Lasso Regression
• k-Nearest Neighbors (k-NN)
• Decision Tree
• Support Vector Machine
• Random Forest
• Extra Trees
• AdaBoost
• Gradient Boost
• XGBoost
• Voting Regressor
• Stacking Regressor

Selected Best Models:

1. Random Forest Regressor
   • R² Score: 88.78%
   • MAE: 15.94
2. Voting Regressor (Random Forest + Gradient Boost)
   • R² Score: 89.27%
   • MAE: 15.37

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