Update app.py

app.py

@@ -1050,6 +1050,22 @@ if query:
             st.video("https://www.youtube.com/watch?v=" + video_ids[2])
     st.markdown("---")
 
+    # Add a section header for useful resources
+    st.header("Learn More About Word2Vec the algorithm behind OncoDigger")
+
+    # Add links to videos and webpages
+    # Add links to videos and webpages
+    st.markdown("""
+        Here are some useful resources to help you learn more about Word2Vec:
+
+        1. [Word2Vec Tutorial - The Skip-Gram Model](http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/) - A blog post by Chris McCormick providing a detailed explanation of the skip-gram model used in Word2Vec.
+        2. [Word2Vec Tutorial Part 2 - Negative Sampling](http://mccormickml.com/2017/01/11/word2vec-tutorial-part-2-negative-sampling/) - A follow-up blog post by Chris McCormick discussing negative sampling in Word2Vec.
+        3. [Efficient Estimation of Word Representations in Vector Space](https://arxiv.org/pdf/1301.3781.pdf) - The original research paper by Mikolov et al. that introduced the Word2Vec algorithm.
+        
+        4. [Word2Vec Tutorial: Vector Representation of Words](https://www.youtube.com/watch?v=64qSgA66P-8) - A YouTube video by Sentdex explaining the Word2Vec algorithm and its implementation in Python.
+        5. [Word2Vec: How to Implement Word2Vec in Python](https://www.youtube.com/watch?v=ISPId9Lhc1g&t=6s) - A YouTube video by Data Talks demonstrating how to implement Word2Vec in Python using the Gensim library.
+        """)
+
 # else:
 #     st.error("The password you entered is incorrect.")