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sparse-group LASSO estimator code translated to matlab from R package "SGL"

This project aims to recreate some of the machine learning methods Nate Silver used in 2016, by using the actual election data and determining how accurate some of these methods were at predicting the final results. The methods we used were Principal Component Analysis, Hierarchical Clustering, Decision Trees, Logistic Regression and Lasso Regul…

The purpose of this paper is to analyze how and how much a film's attributes affect its rating, using several regression techniques.

Sports Analytics in Python

Introduction to Machine Learning & Deep Learning

My personal repository for all of my work for the Battling the Curse of Dimensionality course at UU in the fall of 2021.

Sports Analytics in R (Regularization and DecisionTree based approaches for Regression problems)

A simple regression analysis of house prices in USA with 11 features selected on MECE Framework

The project focuses on the Exploratory Data Analysis (EDA) of the given Performance dataset, which includes marks obtained by students in different subjects.

Implementation of classic machine learning concepts and algorithms from scratch and math behind their implementation.Written in Jupiter Notebook Python

This repository gives you access to the CLIMATEREADY survey dataset containing thermal comfort votes during the 2021 and 2022 heatwave periods in Pamplona, Spain, as well as other relevant parameters self-reported by surveyees (e.g. occupant characteristics and behaviour, key building/dwelling characteristics, sleep problems, heat-related symptoms)

A MLR algorithm that analyzes diabetes data in African Americans to predict a diabetes diagnosis

R Markdown Notebook- Data Analysis and Regression Models in R

Regression Analysis of Used Car Prices

My Data Science senior honors thesis involving Clash Royale

Final project for ECON434

Comparison of car prices between Germany and Czech republic markets by conducting dependency analysis and linear model.