Update pages/6_Feature_Engineering.py

pages/6_Feature_Engineering.py

@@ -76,40 +76,71 @@ st.markdown("""
     </style>
     """, unsafe_allow_html=True)
 
+st.markdown("<h1 class='header-title'>🛠️ Feature Engineering 📌</h1>", unsafe_allow_html=True)
 
-st.header("Feature Engineering📌")
-st.markdown('''
-- When you already have n- no.of features which belongs to collected data and we want to add extra feature where this is automatically engineered made from existing features and the technique of creating the feature is called **feature engineering**
-- There is a sub part in feature engineering known as feature extraction
-''')
+st.markdown(
+    """
+    <div class='info-box'>
+        <p>🔹 When we take **existing features** from collected data and create **new useful features**,where this is automatically engineered made from existing features and the technique of creating the features is known as <span class='highlight'>Feature Engineering</span>.</p>
+        <p>📊 These engineered features **enhance machine learning models**.</p>
+        <p>📍 A subpart of feature engineering is **Feature Extraction**.</p>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
 
-st.subheader(":violet[Feature Extraxtion]")
-st.markdown('''
-- We are having text data which is natural language where the text is given to machine to understand the natural language
-- Text is converted into vector form with feature extraction techniques using algorithms which helps to convert text iinto vector
-- While converting text into vector information should be preserved
-''')
+st.markdown("<h2 class='sub-header'>📥 Feature Extraction</h2>", unsafe_allow_html=True)
 
-st.header("Vectorization🧭")
-st.markdown('''
-- Vectorization is a technique of converting text into vectors
-''')
+st.markdown(
+    """
+    <div class='info-box'>
+        <p>📝 **Feature Extraction** is the process where text data which is natural language is given to machine to understand the natural language.</p>
+        <ul>
+            <li>📜 Text is **converted into vectors** using specific algorithms.</li>
+            <li>🔍 **Preserving meaningful information** is key.</li>
+            <li>⚙️ Helps in better **text analysis & machine learning**.</li>
+        </ul>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
 
-st.subheader("Vectorization techniques")
-st.markdown("""
-    There a different techniques to convert text into vector format.They are :
-    <ul class="icon-bullet">
-        <li>One-Hot Vectorization </li>
-        <li>Bag of Words(BOW) </li>
-        <li>Term Frequency - Inverse Document Frequency(TF-IDF) </li>
-    </ul>
-""", unsafe_allow_html=True)
+st.markdown("<h1 class='header-title'>🧭 Vectorization</h1>", unsafe_allow_html=True)
+st.markdown(
+    """
+    <div class='info-box'>
+        <p>📌 **Vectorization** is the process of converting text into **numerical vectors**.</p>
+        <p>💡 This allows ML models to process text data effectively.</p>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
 
-st.markdown("""
-    There are advance vectorization techniques.They are :
-    <ul class="icon-bullet">
-        <li>Word Embedding </li>
-            <li>Word2Vec </li>
-            <li>Fasttext</li>
-    </ul>
-""", unsafe_allow_html=True)
+st.markdown("<h2 class='sub-header'>🛠️ Vectorization Techniques</h2>", unsafe_allow_html=True)
+st.markdown(
+    """
+    <div class='info-box'>
+        <p>📌 Basic Vectorization Techniques:</p>
+        <ul>
+            <li>🔹 One-Hot Encoding</li>
+            <li>🔹 Bag of Words (BoW)</li>
+            <li>🔹 Term Frequency - Inverse Document Frequency (TF-IDF)</li>
+        </ul>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
+
+st.markdown(
+    """
+    <div class='info-box'>
+        <p>🚀 Advanced Vectorization Techniques:</p>
+        <ul>
+            <li>🌍 Word Embeddings</li>
+                <li>🔠 Word2Vec</li>
+                <li>⚡ FastText</li>
+        </ul>
+    </div>
+    """,
+    unsafe_allow_html=True
+)