Update README.md

README.md

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----
-title: Predictor
-emoji: 💻
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 6.14.0
-python_version: '3.13'
-app_file: app.py
-pinned: false
-license: apache-2.0
-short_description: 'A supervised machine learning workflow '
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Student Placement Predictor
+
+A machine learning web app that predicts whether a student will be selected based on their **CGPA** and **IQ**.
+
+## Demo
+
+Try it live on [Hugging Face Spaces](https://huggingface.co/spaces/jackenmail/predictor)
+
+## How It Works
+
+Enter a student's CGPA and IQ score, and the model predicts:
+- **User will select** — the student is likely to be selected
+- **User will not select** — the student is unlikely to be selected
+
+The model uses a **Logistic Regression** pipeline with **StandardScaler** preprocessing trained on student placement data.
+
+## Inputs
+
+| Field | Description |
+|-------|-------------|
+| CGPA  | Cumulative Grade Point Average (e.g. 7.5) |
+| IQ    | IQ score (e.g. 120) |
+
+## Tech Stack
+
+- [Gradio](https://gradio.app/) — web UI
+- [scikit-learn](https://scikit-learn.org/) — ML model
+- [joblib](https://joblib.readthedocs.io/) — model serialization
+- [NumPy](https://numpy.org/) — numerical processing
+
+## Run Locally
+
+```bash
+pip install -r requirements.txt
+python app.py
+```
+
+Then open `http://localhost:7860` in your browser.
+
+## Files
+
+```
+app.py            # Gradio app and prediction logic
+model.pkl         # Trained scikit-learn pipeline (StandardScaler + LogisticRegression)
+requirements.txt  # Python dependencies
+```