import streamlit as st

st.set_page_config(page_title="AutoML - Classification & Regression", layout="wide")

st.title("Automated Machine Learning (AutoML) Pipeline")
st.subheader("Effortless ML Model Training for Classification & Regression")

st.markdown("""
### 🔹 About the Project
This AutoML project, built using Streamlit and deployed on Hugging Face, simplifies machine learning model training. Users can upload a dataset, and the system will:
- **Detect the problem type** (Classification or Regression)
- **Preprocess the data** (handling missing values, encoding categorical variables, feature scaling, etc.)
- **Train multiple models** automatically
- **Evaluate performance** based on accuracy or other relevant metrics
- **Display results** interactively with visualizations
### 🚀 How It Works
1. **Upload a dataset (CSV format)**
2. **Select the type of machine learning problem** (or let the system auto-detect)
3. **Choose an algorithm** or let the system try multiple models
4. **View model performance and accuracy**
5. **Download the trained model (optional)**
### 📌 Features in Development
- Hyperparameter tuning
- Model interpretability
- Deployment options for trained models
""")