Welcome to MLOps-TripleP, a Python-based project designed to predict solar panel production over university parking areas. This innovative project leverages machine learning models and real-time weather data to provide accurate forecasts, aiding in the optimization of energy consumption and enhancing sustainability efforts. By contributing to MLOps-TripleP, you're participating in a movement towards more informed decision-making in energy management.
This project is made for Spring 2024 MLOps Lecture.
The goal of this project is to learn how to utilize corretly the tools that are typically used in the industry. Every part of the project that we were asked to make is (and will) be compiled in the following table.
| Subject | Link |
|---|---|
| Handwritten Work | PDF's |
| Exploratory Data Analysis (EDA) | EDA |
| Data Modelling | Models |
- Birtles Alixia - alixia.birtles@student.uliege.be
- Delporte Guillaume - guillaume.delporte@student.uliege.be
- Lambermont Romain - romain.lambermont@student.uliege.be
- Louis Arthur - a.louis@student.uliege.be
- Thomas Vrancken (Instructor) - t.vrancken@uliege.be
- Matthias Pirlet (Teaching Assistant) - Matthias.Pirlet@uliege.be
For any inquiries, please reach out to the project team via email or contact the teaching staff directly.
Join us in advancing sustainability and optimizing energy consumption through innovative machine learning solutions with MLOps-TripleP!