AI and Data Science examples 🧠

Github Repository for the Streamlit "AI and Data Science examples" HEC Paris app.

Deploy the app locally using streamlit run main_page.py.

The app currently has four use cases:

Time Series Forecasting on Electrical Power Consumption
Sentiment Analysis on Customer reviews
Recommendation system for movies

Contributor guidelines

Github

Clone the repository locally (git clone)
Create a virtual environment python -m venv <venv_name> ⇒ never push venv folder to github
Install all the package dependencies using pip install -r requirements.txt
Create a branch for each feature/use cases added
Don’t push to the main branch, create a pull request to integrate changes to the repo
Never push .streamlit folder to the repo
Make sure your code is well documented (doc strings for functions,…)

Streamlit

To deploy the app locally, run on the terminal streamlit run main_page.py
Create a page for each use case (in the page\ folder)
Add datasets to the data\ folder
Add pretrained/saved models to the pretrained_models folder
.streamlit : Add API keys, identifications… to a .yaml file (never pushed to the repo, add the “secrets” to the deployed app directly on the website)