[{"data":1,"prerenderedAt":374},["ShallowReactive",2],{"project-artstudies":3},{"id":4,"title":5,"description":6,"extension":7,"favorite":8,"icon":9,"meta":10,"publishedAt":363,"readingTime":364,"shortDescription":365,"slug":366,"status":367,"stem":368,"tags":369,"type":372,"__hash__":373},"projects\u002Fprojects\u002Fartstudies.md","ArtStudies - Academic Projects Collection","A curated collection of mathematics and data science projects developed during my academic journey, spanning Bachelor's and Master's studies.","md",true,"i-ph-book-duotone",{"body":11},{"type":12,"value":13,"toc":357},"minimark",[14,37,40,62,67,193,197],[15,16,17,27,28,32,33,36],"p",{},[18,19,23],"a",{"href":20,"rel":21},"https:\u002F\u002Fgithub.com\u002FArthurDanjou\u002Fartstudies",[22],"nofollow",[24,25,26],"strong",{},"ArtStudies Projects"," is a curated collection of academic projects completed throughout my mathematics studies. The repository showcases work in both ",[29,30,31],"em",{},"Python"," and ",[29,34,35],{},"R",", with a focus on mathematical modeling, data analysis, and numerical methods.",[15,38,39],{},"The projects are organized into three main sections:",[41,42,43,50,56],"ul",{},[44,45,46,49],"li",{},[24,47,48],{},"L3"," – Third year of the Bachelor's degree in Mathematics",[44,51,52,55],{},[24,53,54],{},"M1"," – First year of the Master's degree in Mathematics",[44,57,58,61],{},[24,59,60],{},"M2"," – Second year of the Master's degree in Mathematics",[63,64,66],"h2",{"id":65},"file-structure","File Structure",[41,68,69,116,157],{},[44,70,71,74],{},[72,73,48],"code",{},[41,75,76,81,86,91,96,101,106,111],{},[44,77,78],{},[72,79,80],{},"Analyse Matricielle",[44,82,83],{},[72,84,85],{},"Analyse Multidimensionnelle",[44,87,88],{},[72,89,90],{},"Calculs Numériques",[44,92,93],{},[72,94,95],{},"Équations Différentielles",[44,97,98],{},[72,99,100],{},"Méthodes Numériques",[44,102,103],{},[72,104,105],{},"Probabilités",[44,107,108],{},[72,109,110],{},"Projet Numérique",[44,112,113],{},[72,114,115],{},"Statistiques",[44,117,118,120],{},[72,119,54],{},[41,121,122,127,132,137,142,147,152],{},[44,123,124],{},[72,125,126],{},"Data Analysis",[44,128,129],{},[72,130,131],{},"General Linear Models",[44,133,134],{},[72,135,136],{},"Monte Carlo Methods",[44,138,139],{},[72,140,141],{},"Numerical Methods",[44,143,144],{},[72,145,146],{},"Numerical Optimization",[44,148,149],{},[72,150,151],{},"Portfolio Management",[44,153,154],{},[72,155,156],{},"Statistical Learning",[44,158,159,161],{},[72,160,60],{},[41,162,163,168,173,178,183,188],{},[44,164,165],{},[72,166,167],{},"Data Visualisation",[44,169,170],{},[72,171,172],{},"Deep Learning",[44,174,175],{},[72,176,177],{},"Linear Models",[44,179,180],{},[72,181,182],{},"Machine Learning",[44,184,185],{},[72,186,187],{},"VBA",[44,189,190],{},[72,191,192],{},"SQL",[63,194,196],{"id":195},"technologies-tools","Technologies & Tools",[41,198,199,208,217,227,237,247,257,267,277,287,297,307,317,327,337,347],{},[44,200,201,207],{},[24,202,203],{},[18,204,31],{"href":205,"rel":206},"https:\u002F\u002Fwww.python.org",[22],": A high-level, interpreted programming language, widely used for data science, machine learning, and scientific computing.",[44,209,210,216],{},[24,211,212],{},[18,213,35],{"href":214,"rel":215},"https:\u002F\u002Fwww.r-project.org",[22],": A statistical computing environment, perfect for data analysis and visualization.",[44,218,219,226],{},[24,220,221],{},[18,222,225],{"href":223,"rel":224},"https:\u002F\u002Fjupyter.org",[22],"Jupyter",": Interactive notebooks combining code, results, and rich text for reproducible research.",[44,228,229,236],{},[24,230,231],{},[18,232,235],{"href":233,"rel":234},"https:\u002F\u002Fpandas.pydata.org",[22],"Pandas",": A data manipulation library providing data structures and operations for manipulating numerical tables and time series.",[44,238,239,246],{},[24,240,241],{},[18,242,245],{"href":243,"rel":244},"https:\u002F\u002Fnumpy.org",[22],"NumPy",": Core package for numerical computing with support for large, multi-dimensional arrays and matrices.",[44,248,249,256],{},[24,250,251],{},[18,252,255],{"href":253,"rel":254},"https:\u002F\u002Fwww.scipy.org",[22],"SciPy",": A library for advanced scientific computations including optimization, integration, and signal processing.",[44,258,259,266],{},[24,260,261],{},[18,262,265],{"href":263,"rel":264},"https:\u002F\u002Fscikit-learn.org",[22],"Scikit-learn",": A robust library offering simple and efficient tools for machine learning and statistical modeling, including classification, regression, and clustering.",[44,268,269,276],{},[24,270,271],{},[18,272,275],{"href":273,"rel":274},"https:\u002F\u002Fwww.tensorflow.org",[22],"TensorFlow",": A comprehensive open-source framework for building and deploying machine learning and deep learning models.",[44,278,279,286],{},[24,280,281],{},[18,282,285],{"href":283,"rel":284},"https:\u002F\u002Fkeras.io",[22],"Keras",": A high-level neural networks API, running on top of TensorFlow, designed for fast experimentation.",[44,288,289,296],{},[24,290,291],{},[18,292,295],{"href":293,"rel":294},"https:\u002F\u002Fmatplotlib.org",[22],"Matplotlib",": A versatile plotting library for creating high-quality static, animated, and interactive visualizations in Python.",[44,298,299,306],{},[24,300,301],{},[18,302,305],{"href":303,"rel":304},"https:\u002F\u002Fplotly.com",[22],"Plotly",": An interactive graphing library for creating dynamic visualizations in Python and R.",[44,308,309,316],{},[24,310,311],{},[18,312,315],{"href":313,"rel":314},"https:\u002F\u002Fseaborn.pydata.org",[22],"Seaborn",": A statistical data visualization library built on top of Matplotlib, providing a high-level interface for drawing attractive and informative graphics.",[44,318,319,326],{},[24,320,321],{},[18,322,325],{"href":323,"rel":324},"https:\u002F\u002Frmarkdown.rstudio.com",[22],"RMarkdown",": A dynamic tool for combining code, results, and narrative into high-quality documents and presentations.",[44,328,329,336],{},[24,330,331],{},[18,332,335],{"href":333,"rel":334},"https:\u002F\u002Ffactominer.free.fr\u002F",[22],"FactoMineR",": An R package focused on multivariate exploratory data analysis (e.g., PCA, MCA, CA).",[44,338,339,346],{},[24,340,341],{},[18,342,345],{"href":343,"rel":344},"https:\u002F\u002Fggplot2.tidyverse.org",[22],"ggplot2",": A grammar-based graphics package for creating complex and elegant visualizations in R.",[44,348,349,356],{},[24,350,351],{},[18,352,355],{"href":353,"rel":354},"https:\u002F\u002Fshiny.rstudio.com",[22],"RShiny",": A web application framework for building interactive web apps directly from R.",{"title":358,"searchDepth":359,"depth":359,"links":360},"",2,[361,362],{"id":65,"depth":359,"text":66},{"id":195,"depth":359,"text":196},"2023-09-01",1,"A collection of academic projects in mathematics and data science from my university studies.","artstudies","In progress","projects\u002Fartstudies",[31,35,370,371],"Data Science","Mathematics","Academic Project","mFDxM_hCDUUMP-vQ2Uruc06wGq7pWnw8C0LKlGellXs",1777982163834]