Add Streamlit app for student success prediction and model training script

- Created `streamlit_app.py` for a user-friendly dashboard to predict student outcomes using a Random Forest model.
- Added `requirements.txt` to specify necessary Python packages for the application.
- Implemented `train_and_save_model.py` to train the Random Forest model and save it along with preprocessing information.
- Included detailed user input forms for various student characteristics and academic performance metrics.
- Added custom styling for better UI/UX in the Streamlit app.
- Integrated prediction results display with probability metrics and model performance insig

.gitignore

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+# Data files
+/data/
+*.csv
+
+# Jupyter Notebook checkpoints
+.ipynb_checkpoints/
+
+# Python cache
+__pycache__/
+*.pyc
+
+# Environment files
+.env
+.venv/
+venv/
+env/
+*.env
+
+# VSCode settings
+.vscode/
+
+# MacOS system files
+.DS_Store
+
+# Logs and outputs
+*.log
+*.out
+
+# Model artifacts
+*.pkl
+*.joblib
+*.h5
+
+# Reports and HTML exports
+*.html
+*.pdf
+
+# Temporary files
+*.tmp
+*.bak
+
+# Copilot instructions
+copilot-instructions.md