Data Analytics exam final project, MSc in Computer Science.
By Matteo Coppola, Luca Palazzi, Antonio Vivace.
Exploration, Sentiment Analysis, Topic Analysis (LDA) and a VueJS web application exposing the trained models.
Set up the a Python virtual environment and install required packages
# run this as sudo if it doesn't work
python3 -m spacy download en
cd scripts
python3 -m venv .
source bin/activate
pip3 install -r requirements.txt
Optionally, install a ipynb kernel to use the venv packages
pip3 install --user ipykernel
python -m ipykernel install --user --name=myenv
# Check the installed kernels
jupyter kernelspec list
# Run Jupyter
jupyter lab
Now, to run the full pipeline:
python3 main.py
A Flask application exposes a simple API (on port 5000) allowing the trained models to be used on demand via simple HTTP requests (in main.py). The VueJS application needs a recent version of NodeJS and npm.
cd webapp
npm install
# serve the web application with hot reload
npm run serve
Antuz notes: accent is #B71C1C
, typeface is Barlow 500. On the plots and graphs, typeface is Inter 600, palette is #4DAF4A
, #FF7F00
, #C73E31
.