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import streamlit as st
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import sklearn
from io import StringIO
# main page
custom_css = """
<style>
html, body, [data-testid="stAppViewContainer"] {
background:url('https://images.pexels.com/photos/1435752/pexels-photo-1435752.jpeg?auto=compress&cs=tinysrgb&w=600') no-repeat center center fixed;
background-size: cover; /* Cover the entire screen */
font-family: Arial, sans-serif;
color: #333333;
}
</style>"""
# Apply custom CSS
st.markdown(custom_css, unsafe_allow_html=True)
st.markdown('<div style="text-align: center"><h1>CLASSIFICATION MODEL</h1></div>', unsafe_allow_html=True)
st.markdown('<h2>Upload the Classification Dataset</h2>',unsafe_allow_html=True)
st.file_uploader(label="Choose a file to upload",type=["csv","xlsx","json","txt"])
options = ["Info About the DataSet", "Pre-Processing"]
selection = st.pills("Directions", options, selection_mode="multi")
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