Update pages/7_Advance_vectorization_techniques.py

pages/7_Advance_vectorization_techniques.py

@@ -144,4 +144,67 @@ st.markdown('''
 ''')
 
 if file_type == "Word2Vec":
-    st.title(":red[Word2Vec]")
+    st.title(":red[Word2Vec]")
+    st.markdown(
+    """
+    <div class='box'>
+        <h3 style='color: #6A0572;'>📌 How Word2Vec Works?</h3>
+        <ul>
+            <li>After <strong>training</strong>, we obtain the final <span class='highlight'>Word2Vec model</span></li>
+            <li>The model stores a <strong>dictionary</strong> with word-vector pairs:</li>
+        </ul>
+        <pre style="background-color:#F7F7F7; padding: 10px; border-radius: 5px;">
+        { w1: [v1], w2: [v2], w3: [v3] }
+        </pre>
+    </div>
+    """,
+    unsafe_allow_html=True,
+    )
+    st.markdown(
+    """
+    <div class='box'>
+        <h3 style='color: #6A0572;'>⚙️ Training vs. Test Time</h3>
+        <ul>
+            <li><strong>Training Time</strong>: <span class='highlight'>Corpus + Deep Learning Algorithm</span> → Generates Model</li>
+            <li><strong>Test Time</strong>: <span class='highlight'>Word</span> → Looked up in Dictionary → Returns <span class='highlight'>Vector Representation</span></li>
+        </ul>
+    </div>
+    """,
+    unsafe_allow_html=True,
+    )
+
+    st.markdown(
+    """
+    <div class='box'>
+        <h3 style='color: #6A0572;'>🔍 How Does It Preserve Meaning?</h3>
+        <ul>
+            <li>It learns from the <strong>context</strong> of words in the <span class='highlight'>corpus</span></li>
+            <li>When given a word, it checks in the dictionary and retrieves the <strong>semantic vector</strong></li>
+            <li>Unlike other models, <span class='highlight'>dimensions are not words</span>, but their meanings</li>
+        </ul>
+    </div>
+    """,
+    unsafe_allow_html=True,
+    )
+
+    st.markdown(
+    """
+    <div class='box'>
+        <h3 style='color: #6A0572;'>📚 Why is Corpus Important?</h3>
+        <ul>
+            <li>The <strong>Word2Vec algorithm</strong> is completely dependent on the corpus</li>
+            <li>Better corpus → Better word representation</li>
+            <li>It <strong>preserves semantic meaning</strong> using neighborhood words (context)</li>
+        </ul>
+    </div>
+    """,
+    unsafe_allow_html=True,
+    )
+    st.markdown(
+    """
+    <div class='formula'>
+        <strong>Word2Vec understands words by their meaning, not just their presence! 🚀</strong>
+    </div>
+    """,
+    unsafe_allow_html=True,
+    )