KrispyKarim commited on
Commit
7ccac6f
·
verified ·
1 Parent(s): a6c2ded

Upload 4 files

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ pictures/karim[[:space:]]1.jpg filter=lfs diff=lfs merge=lfs -text
pages/01_BERT_Topic_Modeling.py ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import streamlit as st
2
+
3
+ def bert_intro():
4
+ st.title("Topic Modeling with BERT")
5
+ st.markdown("BERT (BERTopic): Explanation of the advanced NLP technique used for analyzing the data, and its application in this project.")
6
+
7
+ st.header("Process Flow: Step-by-step breakdown of the analysis process, from data gathering to insights extraction.")
8
+
9
+ def youth_classification():
10
+ st.title("Youth Classification")
11
+
12
+ def sentiment_analysis():
13
+ st.title("Sentiment Analysis")
14
+
15
+ def bert_topic_modeling():
16
+ st.title("Topic Modeling")
17
+
18
+ sidebar_pages = ["Introduction", "Youth Classification", "Sentiment Analysis", "Topic Modeling"]
19
+ def main():
20
+ st.sidebar.title("Navigation")
21
+ page = st.sidebar.selectbox("Select page:", sidebar_pages)
22
+
23
+ if page == "Introduction":
24
+ bert_intro()
25
+ elif page == "Youth Classification":
26
+ youth_classification()
27
+ elif page == "Sentiment Analysis":
28
+ sentiment_analysis()
29
+ elif page == "Topic Modeling":
30
+ bert_topic_modeling()
31
+
32
+ if __name__ == "__main__":
33
+ main()
pages/02_Initial_Topic_Modeling.py ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import streamlit as st
2
+ import streamlit.components.v1 as components
3
+
4
+ st.title("Topic Modeling")
5
+
6
+ def introduction():
7
+ st.title("Research & Methodology")
8
+ st.markdown("LDA as Baseline: "
9
+ "Describe the use of Latent Dirichlet Allocation as a baseline for comparison and understanding.")
10
+ st.markdown("Process Flow: Step-by-step breakdown of the analysis process, from data gathering to insights extraction.")
11
+
12
+ # Display the LDA visualization HTML file
13
+ components.html(open('lda_visualization.html', 'r').read(), height=800)
14
+
15
+
16
+ def lda_page():
17
+ st.title("Insights & Findings of Latent Dirichlet Allocation (LDA) Model")
18
+ st.markdown("Priliminary Results: findings, notebooks, documentation")
19
+ st.markdown("Visualizations including pyLDAvis: ")
20
+ st.markdown("Key Trends: ")
21
+
22
+ sidebar_pages = ["Introduction", "Latent Dirichlet Allocation"]
23
+ def main():
24
+ st.sidebar.title("Navigation")
25
+ page = st.sidebar.selectbox("Select a page:", sidebar_pages)
26
+
27
+ if page == "Introduction":
28
+ introduction()
29
+ elif page == "Latent Dirichlet Allocation":
30
+ lda_page()
31
+
32
+ if __name__ == "__main__":
33
+ main()
pages/03_Contact.py ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import streamlit as st
2
+ from PIL import Image # for pictures
3
+
4
+ st.title('Contact')
5
+
6
+ st.markdown("Project Team: Introduction to the project team, including brief bios or links to their profiles.")
7
+ st.markdown("Contact Info: social media, contact form, emails")
8
+
9
+
10
+ ### Pictures
11
+ photo_karim = Image.open(r"C:pictures\karim 1.jpg")
12
+ st.image(photo_karim, caption="horizontal Picture of Karim (default width)", width=None, use_column_width=None, clamp=False, channels="RGB",
13
+ output_format="auto", use_container_width=False)
14
+ st.header("FAQ")
pictures/karim 1.jpg ADDED

Git LFS Details

  • SHA256: 494d2a1649a321881781b5d18e22c4fd01860fb21917287bd78cd5ed177fb28f
  • Pointer size: 132 Bytes
  • Size of remote file: 2.71 MB