This Flask web application leverages machine learning models to predict campus placements based on user-provided input. It provides an intuitive and user-friendly interface for users to input relevant features, such as academic performance, gender, work experience, and more. The application then processes these inputs through a trained machine learning model to generate predictions regarding the likelihood of placement.
- Predict campus placements using a machine learning model.
- User-friendly interface for inputting details.
- Responsive design for a seamless user experience.
- Python 3.x
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Clone the repository:
git clone https://github.com/ronakbediya310/Campus-Placement-Project.git
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Change into the project directory: cd campus-placement-prediction
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install dependencies pip install -r rquirements.txr
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Run flask app: python app.py
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Open your browser and navigate to http://localhost:5000.
Usage: Enter the required details in the prediction form. Click the "Predict" button. View the prediction result.
Training Pipeline: Explain how to train machine learning models using the provided training pipeline.
Prediction Pipeline: Detail how to make predictions using the prediction pipeline.
Exception Handling Describe the custom exception handling implemented in the project.
Logging: Explain how logging is implemented in the project and where log files can be found.
result page
