In the student performance prediction project, I utilized simple machine learning techniques and applied hyperparameter tuning using grid search CV to fine-tune and select the best machine learning model for predicting student performance in examinations.
For run this code need python environment
For Create a venv
python -m venv <venv_name>
For activate venv(macos)
source <venv_name>/bin/activate
For activate venv(Windows)
.\venv\Scripts\activate.bat
After creating a virtual environment, run the predict method inside the src/pipeline/predict_pipeline.py file.