I'm Lorenzo Cesari, of the University of Bologna. I'm 25 years old and nearing the completion of my master's program in data science in July 2022.
This project is inspired from the paper Impact of COVID-19 emergency on residential water end-use consumption measured with a high-resolution IoT system by A. Di Mauro; G. F. Santonastaso; S. Venticinque; A. Di Nardo.
They develop exploratory contents of the data for understanding how the pandemic has affected the behavior of water users and their water consumption.
You can find a copy of the paper also in the reference folder.
Through the exploratory analysis, I explore in more detail the differences in water consumption between workers and smart workers.
My project contains a lot of interactive plots from which you can isolate and visualize your data portions of interest.
I also asked myself a Machine Learning problem and tried to solve it as well as I could.
It included pre-processing pipelines, supervised learning models, training and testing, and Ensamble learning techniques.
In conclusion, I describe a real case scenario in which my machine learning model may be useful, and how it can be implemented.
The README.md files that are present in each folder explain briefly what each folder contains.
The core of the project is the scripts folder.
The interactive features of the notebooks, such as within links, will not properly work well in GitHub repositories, so, for pretty view, I suggest to copy the URLs of the notebooks in nbviewer.