Update pages/6_Feature_Engineering.py

pages/6_Feature_Engineering.py

@@ -137,8 +137,21 @@ st.markdown("""
 st.sidebar.title("Navigation 🧭")
 file_type = st.sidebar.radio(
     "Choose a Vectorization technique :",
-    ("One-Hot Vectorization", "Bag of Words(BOW)", "Term Frequency - Inverse Document Frequency(TF-IDF)", "Word2Vec", "Fasttext"))
+    ("One-Hot Vectorization", "Bag of Words(BOW)", "Term Frequency - Inverse Document Frequency(TF-IDF)"))
 
 if file_type == "One-Hot Vectorization":
-    st.title("One-Hot Vectorization")
+    st.title(":red[One-Hot Vectorization]")
+    st.markdown('''
+    - It is type of vectorization technique where we can convert text into vector
+    - Steps in One-Hot vectorization
+    - 1. Create a vocabulary (set of all unique words in collected corpus)
+    - 2. Find the length of the vocabulary
+    - 3. Converting every document into vector form
+        - Every unique word into vector (where vector will have → d-dimension → len(vocabulary))
+        - Every dimension belongs to unique word 
+    - Here we're not converting document into vector , we're converting each and every word to vector form and then combining it to form vector
+    - This technique is called One-Hot Vectorization
+    ''')
+
+