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🚆 Train Route Analysis and Journey Duration Prediction

📌 Project Overview

This project analyzes railway route data and builds a machine learning model to predict journey duration.

🔧 Technologies Used

  • Python
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Scikit-learn

📊 Project Workflow

  1. Data Cleaning and Preprocessing
  2. Feature Engineering
  3. Exploratory Data Analysis (EDA)
  4. Model Building using Linear Regression
  5. Model Evaluation (MAE, RMSE)
  6. Visualization of Actual vs Predicted Journey Duration

📈 Key Features Engineered

  • Journey Duration (in hours)
  • Total Distance per Train
  • Number of Stops
  • Average Speed

🤖 Model Used

Linear Regression

📌 Results

  • Strong correlation between distance and journey duration
  • Number of stops impacts travel time
  • Model provides reasonable prediction accuracy

🚀 Future Improvements

  • Use advanced models (Random Forest, XGBoost)
  • Deploy using Flask or Streamlit
  • Add real-time railway data

👨‍💻 Author

Nanda Kumar S


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This project analyzes railway route data and builds a machine learning model to predict journey duration.

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