Update pages/Introduction.py

pages/Introduction.py

@@ -13,7 +13,7 @@ st.markdown("<p>NLP powers many applications that use language, such as text tra
 st.subheader("NLP Techniques")
 st.markdown("<p>NLP encompasses a wide array of techniques that aimed at enabling computers to process and understand human language. These tasks can be categorized into several broad areas, each addressing different aspects of language processing. Here are some of the key NLP techniques:</p>",unsafe_allow_html= True)
 
-st.markdown('<p style="color:lightyellow;"><b>1. Text Processing and Preprocessing In NLP</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:blue;"><b>1. Text Processing and Preprocessing In NLP</b></p>', unsafe_allow_html=True)
 st.write("Before performing any analysis or modeling, raw text data must be cleaned and prepared.")
 st.markdown('<p style="color:lightcoral;"><b>a. Tokenization</b></p>', unsafe_allow_html=True)
 st.write("Splits text into smaller units like words or sentences.")
@@ -25,27 +25,27 @@ st.write("Example: _'I love NLP'_ → [‘I’, ‘love’, ‘NLP’]")
 st.write("**(ii) Sentence Tokenization:** Breaking text into sentences.")
 st.write("Example: _'I love NLP. It’s fascinating!'_ → [‘I love NLP.’, ‘It’s fascinating!’]")
 
-st.markdown('<p style="color:lightcoral;"><b>b. Stopword Removal</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:lightblue;"><b>b. Stopword Removal</b></p>', unsafe_allow_html=True)
 st.write("Removes common words like “the,” “and,” “is” that do not contribute much to analysis.")
 
 
-st.markdown('<p style="color:lightcoral;"><b>c. Stemming and Lemmatization</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:lightblue;"><b>c. Stemming and Lemmatization</b></p>', unsafe_allow_html=True)
 st.write("Stemming: Reduces words to their base or root form by chopping off suffixes (may not produce valid words).")
 st.write("Example: _“running” _ → “run”")
 
 st.write("Lemmatization: Converts words to their base form using vocabulary and grammar")
 st.write("Example: _“good” _ → “better”")
 
-st.markdown('<p style="color:lightcoral;"><b>d. Part-of-Speech (POS) Tagging</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:lightblue;"><b>d. Part-of-Speech (POS) Tagging</b></p>', unsafe_allow_html=True)
 st.write("Labels words with their grammatical roles (noun, verb, adjective, etc.)")
 st.write("Example: _The cat sleeps”_ → [“The/DET”, “cat/NOUN”, “sleeps/VERB”]")
 
-st.markdown('<p style="color:lightcoral;"><b>e. Named Entity Recognition (NER)</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:lightblue;"><b>e. Named Entity Recognition (NER)</b></p>', unsafe_allow_html=True)
 st.write("Identifies and classifies entities in text (e.g., names, dates, locations)")
 st.write("Example: _ “Barack Obama was born in Hawaii. _ ” → [Barack Obama: PERSON, Hawaii: LOCATION]")
 
 
-st.markdown('<p style="color:lightcoral;"><b>f. Text Normalization</b></p>', unsafe_allow_html=True)
+st.markdown('<p style="color:lightblue;"><b>f. Text Normalization</b></p>', unsafe_allow_html=True)
 st.write("Converts text to a standard format (lowercasing, removing punctuation, etc.).")