second commit

README.md

@@ -1,66 +1,10 @@
-# 🏆 Iris Flower Classification with Decision Tree
-
-> **A simple machine learning project to classify Iris flowers using a Decision Tree model, built with Flask and Docker.**
-
-
-## 🚀 Project Overview
-This project demonstrates how to build, train, and deploy a Decision Tree classifier for the famous Iris flower dataset. The model is served as a REST API using Flask, and can be containerized with Docker for easy deployment.
-
-## 📂 Project Structure
-
-- `app.py` — Flask API for model inference
-- `decision_tree_model.pkl` — Trained Decision Tree model
-- `Tugas_12_Iris_Flower_Classification_with_Decision_Tree.ipynb` — Jupyter Notebook for EDA, training, and evaluation
-- `requirements.txt` — Python dependencies
-- `Dockerfile` — Containerization setup
-- `README.md` — Project documentation
-
-## 📝 How to Run Locally
-
-1. **Clone the repository**
-2. **Create a virtual environment & install dependencies**
-   ```bash
-   python -m venv venv
-   venv\Scripts\activate
-   pip install -r requirements.txt
-   ```
-3. **Train the model (if not already trained)**
-   - Run the notebook `Tugas_12_Iris_Flower_Classification_with_Decision_Tree.ipynb` to generate `decision_tree_model.pkl`.
-4. **Start the Flask API**
-   ```bash
-   python app.py
-   ```
-5. **Test the API**
-   - Send a POST request to `http://localhost:7860/predict` with JSON body:
-     ```json
-     { "data": [5.1, 3.5, 1.4, 0.2] }
-     ```
-   - Response:
-     ```json
-     { "prediksi_spesies": "setosa" }
-     ```
-
-## 🐳 Run with Docker
-
-1. **Build the Docker image**
-   ```bash
-   docker build -t iris-dt-api .
-   ```
-2. **Run the container**
-   ```bash
-   docker run -p 7860:7860 iris-dt-api
-   ```
-
-## 📊 Notebook Features
-- Exploratory Data Analysis (EDA)
-- Model training & evaluation
-- Visualization of the Decision Tree
-- Model export with `joblib`
-
-## 📚 References
-- [Scikit-learn Iris Dataset](https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html)
-- [Flask Documentation](https://flask.palletsprojects.com/)
-- [Docker Documentation](https://docs.docker.com/)
-
 ---
-*Made with ❤️ for educational purposes.*
+title: Classification With Decision Tree
+emoji: 🏆
+colorFrom: green
+colorTo: indigo
+sdk: docker
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference