Update pages/Introduction.py

pages/Introduction.py

@@ -49,10 +49,10 @@ st.markdown('<p style="color:blue;"><b>f. Text Normalization</b></p>', unsafe_al
 st.write("Converts text to a standard format (lowercasing, removing punctuation, etc.).")
 
 
-st.markdown('<p style="color:yellow;"><b>2. Feature Extraction Techniques</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:blue;"><b>2. Feature Extraction Techniques</b></p>', unsafe_allow_html=True)
 st.write("Text needs to be transformed into numerical representations for machine learning models.")
 
-st.markdown('<p style="color:blue;"><b>Bag of Words (BoW)</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:blue;"><b>a. Bag of Words (BoW)</b></p>', unsafe_allow_html=True)
 st.write("Represents text as a vector of word frequencies or occurrences, ignoring grammar and order")
 st.write("Examples:")
 st.write("Text: “I love NLP” and “NLP is great”")
@@ -60,3 +60,12 @@ st.write("Vocabulary: [“I”, “love”, “NLP”, “is”, “great”]")
 st.write("Vector for “I love NLP”: [1, 1, 1, 0, 0]")
 
 
+st.markdown('<p style="color:blue;"><b>b. Term Frequency-Inverse Document Frequency (TF-IDF)</b></p>', unsafe_allow_html=True)
+st.write("Assigns weights to words based on their frequency in a document and their rarity across all documents.")
+st.write("Examples:")
+st.write("Text: “I love NLP” and “NLP is great”")
+st.write("Vocabulary: [“I”, “love”, “NLP”, “is”, “great”]")
+st.write("Vector for “I love NLP”: [1, 1, 1, 0, 0]")
+
+
+