Student Placement Prediction Using Machine Learning

Before you download

Student Placement Prediction Using Machine Learning is a web-based mini project that predicts whether a student is likely to get placed based on academic and skill-related information. The system considers inputs such as CGPA, internships, projects, certifications, aptitude score, communication skills and backlogs. A Machine Learning model processes these details and provides a placement prediction along with the probability. The project includes dataset handling, model training, prediction and a simple Flask-based web interface. It is suitable for students who want to understand the practical implementation of Machine Learning with Python and Flask.

Getting started

1. Download and extract the project ZIP file.

2. Open the extracted project folder in Command Prompt or VS Code Terminal.

3. Create a virtual environment:

py -m venv venv

4. Activate the virtual environment:

venv\Scripts\activate

5. Install the required packages:

pip install -r requirements.txt

6. Train the Machine Learning model:

python train_model.py

7. Start the Flask application:

python app.py

8. Open your browser and visit:

http://127.0.0.1:5000

9. Enter the student details and click the prediction button to view the placement prediction.

Requirements

• Python 3.9 or above
• pip
• Flask
• Pandas
• NumPy
• Scikit-learn
• Joblib
• Web browser
• VS Code or any Python IDE (optional)

Build your understanding

Use this resource as a learning reference. Explore how the code works, test it with your own inputs and document your changes for your presentation.