msancor/FDS-HW2

Python project for the Fundamentals of of Data Science class for the MSc. in Data Science at the Sapienza University of Rome. The main purpose of the project is exploring Logistic Regression & Multinomial Regression concepts along with training classifiers using Gradient Descent/Ascent.

Fundamental Methods for Data Science - Homework 2

What's inside this repository?

1. README.md: A markdown file that explains the content of the repository.
2. HW2.ipynb: A Jupyter Notebook file containing all the relevant exercises of the homework.
3. .gitignore: A predetermined .gitignore file that tells Git which files or folders to ignore in a Python project.
4. LICENSE: A file containing an MIT permissive license.

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Authors:

• Miguel Angel Sanchez Cortes sanchezcortes.2049495@studenti.uniroma1.it
• Pasquale Luca Tommasino tommasino.1912107@studenti.uniroma1.it
• Sofia Noemi Crobeddu sofianoemi.crobeddu@gmail.com
• Gabriele Volzone volzone.1917002@studenti.uniroma1.it
• Laura Lopez Sanchez laura.lopez@alum.esci.upf.edu

MSc. in Data Science, Sapienza University of Rome