Update pages/DIFFERENCES_BETWEEN_ML&DL.py
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pages/DIFFERENCES_BETWEEN_ML&DL.py
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import streamlit as st
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# Static background image URL
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# Dynamic CSS
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custom_css = """
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<style>
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html, body, [data-testid="stAppViewContainer"] {
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background: linear-gradient(
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rgba(0, 0, 0, 0.6),
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rgba(0, 0, 0, 0.6)
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),
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url("https://cdn.pixabay.com/photo/2023/11/23/17/47/sunset-7704533_1280.jpg") no-repeat center center fixed;
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background-size: cover;
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font-family: Arial, sans-serif;
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color: #ffffff;
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}
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h1 {
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color: #ffffff;
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text-align: center;
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font-size: 2rem;
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margin-top: 2px;
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text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.7);
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}
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.division {
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margin: 20px auto;
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padding: 20px;
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background: rgba(255, 255, 255, 0.1);
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border-radius: 10px;
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
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}
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.division h2 {
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color: #ffffff;
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margin-bottom: 10px;
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font-size: 2rem;
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text-shadow: 1px 1px 3px rgba(0, 0, 0, 0.7);
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}
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.division p, .division ul li {
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font-size: 1.2rem;
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line-height: 1.7;
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}
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</style>
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"""
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# Inject CSS into Streamlit app
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st.markdown(custom_css, unsafe_allow_html=True)
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# Header Section
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st.markdown("<h1>DIFFERENCES BETWEEN ML AND DL</h1>", unsafe_allow_html=True)
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st.markdown(
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"""
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<div class="division">
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<h2>The points in machine learning?</h2>
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<p>
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</p>
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<ul>
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<li><strong>Data Points:</strong>Can train only on small data points .</li>
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<li><strong>Hardware for Training:</strong>Can train on CPU.</li>
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<li><strong>Training Time:</strong>Requires less time due to smaller sizes.</li>
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<li><strong>Algorithm Complexity:</strong>Machine learning algorithms can range from simple linear models to more complex models such as decision trees and random forests..</li>
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<li><strong>Analysis Complexity:</strong>Involves training algorithm to identify patterns and relationship in data..</li>
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<li><strong>Application Areas:</strong>It is used for a wide range of applications, such as regression, classification, and clustering.</li>
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</ul>
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</div>
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""",
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unsafe_allow_html=True
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)
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