app.py

import streamlit as st
import base64

# Set page config
st.set_page_config(page_title="Neural Network Playground", layout="centered")

# Load and encode background image
def get_base64(file_path):
    with open(file_path, "rb") as f:
        data = f.read()
    return base64.b64encode(data).decode()

img_base64 = get_base64("neuron.webp")  # Make sure this image is in the same folder

# Inject CSS with base64 background
st.markdown(
    f"""
    <style>
    .stApp {{
        background-image: url("data:image/jpg;base64,{img_base64}");
        background-size: cover;
        background-position: center;
        background-repeat: no-repeat;
        background-attachment: fixed;
    }}
    </style>
    """,
    unsafe_allow_html=True
)

# Title
st.markdown(
    """
    <h1 style='text-align: center; color: #FF6347; font-weight: bold;'>
        Neural Network Playground
    </h1>
    """,
    unsafe_allow_html=True
)

# Subtitle
st.markdown(
    """
    <h3 style='text-align: center; color: #2E8B57; font-weight: normal;'>
        Dive into the world of neural networks—explore and train with ease!
    </h3>
    """,
    unsafe_allow_html=True
)

# About section
st.subheader("🔎 :blue[About the App:]")

st.markdown("""
Neural Network Playground is an interactive tool designed for hands-on exploration of machine learning models.

Whether you're just starting or already exploring advanced concepts, this platform lets you:

- 🧑‍💻 Build and visualize neural networks with ease and fun.
- 🔬 Train models on interactive datasets with real-time updates.
- 🛠️ Experiment with various architectures and see instant results.
- 🧠 Adjust hyperparameters and observe their effects on model learning—live!

No coding required. Just pure, interactive learning.
""")