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Update pages/Machine Learning vs Deep Learning.py
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pages/Machine Learning vs Deep Learning.py
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@@ -2,35 +2,35 @@ import streamlit as st
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# Adding the introduction part
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st.markdown("""
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<p style='font-size:
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""", unsafe_allow_html=True)
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# Adding the analogy heading
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st.markdown("<h2 style='color: #3498DB; font-size:
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# Adding the analogy content
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st.markdown("""
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<p style='font-size:
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<ul style='font-size:
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<li><b>A recipe book</b> is used for <i>guidance</i>, as it provides clear instructions on how to prepare the dish. You can follow the steps and make adjustments to improve your skills over time.</li>
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<li><b>A set of cooking tools</b> is used for <i>precision</i>, as it allows you to directly manipulate ingredients and execute complex techniques, making it easier to experiment and achieve finer results.</li>
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</ul>
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<p style='font-size:
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<ul style='font-size:
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<li><b>Recipe Book = Machine Learning</b> </li>
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<li><b>Cooking Tools = Deep Learning</b></li>
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</ul>
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""", unsafe_allow_html=True)
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# Adding the table comparison content
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st.markdown("<h2 style='color: #3498DB; font-size:
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markdown_content = """
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<style>
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table {
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font-size:
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width: 100%;
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border-collapse: collapse;
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}
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# Adding the introduction part
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st.markdown("""
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<p style='font-size: 18px;'>Earlier, we discussed how <b>Machine Learning (ML)</b> and <b>Deep Learning (DL)</b> are two powerful tools in the field of <b>Artificial Intelligence (AI)</b>. But how do we better understand their differences? Let’s use an analogy:</p>
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""", unsafe_allow_html=True)
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# Adding the analogy heading
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st.markdown("<h2 style='color: #3498DB; font-size: 25px; font-weight: bold;'>✨ Imagine This: Chefs in the Kitchen </h2>", unsafe_allow_html=True)
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# Adding the analogy content
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st.markdown("""
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<p style='font-size: 18px;'>Two chefs are in the same kitchen. One chef is highly skilled and prepares a dish every day, experimenting with different flavors and ingredients. The second chef, who is not very experienced, wants to recreate the dish but hasn’t been as consistent with their practice. To do this, they borrow the first chef's recipe to copy it. To help them recreate the dish, they use two tools: a <b>recipe book</b> and a <b>set of cooking tools</b>. While both tools serve the same purpose of helping them cook, their functionality differs:</p>
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<ul style='font-size: 18px;'>
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<li><b>A recipe book</b> is used for <i>guidance</i>, as it provides clear instructions on how to prepare the dish. You can follow the steps and make adjustments to improve your skills over time.</li>
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<li><b>A set of cooking tools</b> is used for <i>precision</i>, as it allows you to directly manipulate ingredients and execute complex techniques, making it easier to experiment and achieve finer results.</li>
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</ul>
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<p style='font-size: 18px;'><b>ML and DL Analogy:</b></p>
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<ul style='font-size: 18px;'>
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<li><b>Recipe Book = Machine Learning</b> </li>
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<li><b>Cooking Tools = Deep Learning</b></li>
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</ul>
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""", unsafe_allow_html=True)
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# Adding the table comparison content
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st.markdown("<h2 style='color: #3498DB; font-size: 25px; font-weight: bold;'> Machine Learning vs Deep Learning </h2>", unsafe_allow_html=True)
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markdown_content = """
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<style>
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table {
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font-size: 18px;
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width: 100%;
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border-collapse: collapse;
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}
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