From 6e648526d44848651f69c368a50d83b96e4b8d12 Mon Sep 17 00:00:00 2001 From: Arthur Danjou Date: Fri, 3 Oct 2025 11:33:25 +0200 Subject: [PATCH] Revise ArtStudies project details and technologies Updated project description and added M2 section with new technologies. --- content/projects/artstudies.md | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/content/projects/artstudies.md b/content/projects/artstudies.md index a2f6e9d..870117a 100644 --- a/content/projects/artstudies.md +++ b/content/projects/artstudies.md @@ -11,11 +11,14 @@ tags: - r --- -[ArtStudies](https://go.arthurdanjou.fr/artstudies) is a curated collection of academic projects completed throughout my mathematics studies. The repository showcases work in both _Python_ and _R_, focusing on mathematical modeling, data analysis, and numerical methods. +# ArtStudies + +[ArtStudies Projects](https://github.com/ArthurDanjou/artstudies) is a curated collection of academic projects completed throughout my mathematics studies. The repository showcases work in both _Python_ and _R_, focusing on mathematical modeling, data analysis, and numerical methods. The projects are organized into two main sections: - **L3** – Third year of the Bachelor's degree in Mathematics - **M1** – First year of the Master's degree in Mathematics +- **M2** – Second year of the Master's degree in Mathematics ## 📁 File Structure @@ -38,6 +41,10 @@ The projects are organized into two main sections: - `Portfolio Management` - `Statistical Learning` +- `M2` + - `Machine Learning` + - `SQL` + ## 🛠️ Technologies & Tools - [Python](https://www.python.org): A high-level, interpreted programming language, widely used for data science, machine learning, and scientific computing. @@ -49,6 +56,8 @@ The projects are organized into two main sections: - [Scikit-learn](https://scikit-learn.org): A robust library offering simple and efficient tools for machine learning and statistical modeling, including classification, regression, and clustering. - [TensorFlow](https://www.tensorflow.org): A comprehensive open-source framework for building and deploying machine learning and deep learning models. - [Matplotlib](https://matplotlib.org): A versatile plotting library for creating high-quality static, animated, and interactive visualizations in Python. +- [Plotly](https://plotly.com): An interactive graphing library for creating dynamic visualizations in Python and R. +- [Seaborn](https://seaborn.pydata.org): A statistical data visualization library built on top of Matplotlib, providing a high-level interface for drawing attractive and informative graphics. - [RMarkdown](https://rmarkdown.rstudio.com): A dynamic tool for combining code, results, and narrative into high-quality documents and presentations. - [FactoMineR](https://factominer.free.fr/): An R package focused on multivariate exploratory data analysis (e.g., PCA, MCA, CA). - [ggplot2](https://ggplot2.tidyverse.org): A grammar-based graphics package for creating complex and elegant visualizations in R.