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import os | |
import streamlit as st | |
import pandas as pd | |
import numpy as np | |
from st_pages import Page, show_pages | |
from PIL import Image | |
#from utils import authenticate_drive | |
################################################################################## | |
# PAGE CONFIGURATION # | |
################################################################################## | |
st.set_page_config(layout="wide") | |
################################################################################## | |
# GOOGLE DRIVE CONNEXION # | |
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# if ["drive_oauth"] not in st.session_state: | |
# st.session_state["drive_oauth"] = authenticate_drive() | |
# drive_oauth = st.session_state["drive_oauth"] | |
################################################################################## | |
# TITLE # | |
################################################################################## | |
st.image("images/AI.jpg") | |
st.title("AI and Data Science Examples") | |
st.subheader("HEC Paris, 2023-2024") | |
st.markdown("Course provided by **Shirish C. SRIVASTAVA**") | |
st.markdown(" ") | |
st.info("""**About the app**: The AI and Data Science Examples app was created to introduce students to the field of Data Science by showcasing real-life applications of AI. | |
It includes use cases using traditional Machine Learning algorithms on structured data, as well as Deep Learning models run on unstructured data (text, images,...).""") | |
st.divider() | |
#Hi! PARIS collaboration mention | |
st.markdown(" ") | |
image_hiparis = Image.open('images/hi-paris.png') | |
st.image(image_hiparis, width=150) | |
url = "https://www.hi-paris.fr/" | |
st.markdown("**The app was made in collaboration with: [Hi! PARIS Engineering Team](%s)**" % url) | |
################################################################################## | |
# DASHBOARD/SIDEBAR # | |
################################################################################## | |
# AI use case pages | |
show_pages( | |
[ | |
Page("main_page.py", "Home Page", "π "), | |
Page("pages/supervised_unsupervised_page.py", "Supervised vs Unsupervised", "π"), | |
Page("pages/timeseries_analysis.py", "Time Series Forecasting", "π"), | |
Page("pages/sentiment_analysis.py", "Sentiment Analysis", "π"), | |
Page("pages/object_detection.py", "Object Detection", "πΉ"), #need to reduce RAM costs | |
Page("pages/recommendation_system.py", "Recommendation system", "π") | |
] | |
) | |
################################################################################## | |
# PAGE CONTENT # | |
################################################################################## | |