This repository contains implementations of Decision Tree, Logistic Regression, and Naïve Bayes models applied to the Iris and MTCars datasets. It explores classification and regression tasks, hyperparameter tuning, and performance evaluation using accuracy and RMSE, with visualizations for model interpretation.

This R script analyzes the "mtcars" dataset, exploring variables like mpg, cylinder count, and horsepower. It visualizes the data and identifies the most fuel-efficient car model based on mpg, while also comparing average mpg between automatic and manual transmission cars.

A shiny app for exploring regression relations on mtcars data

This project explores and implements machine learning regression techniques to predict a car's fuel efficiency (measured in miles per gallon, mpg) using the classic mtcars dataset. It follows the CRISP-ML methodology, covering data preprocessing, exploratory data analysis (EDA), model training, evaluation, and deployment.

Exploring mtcars

exploring the mtcars dataset

Exploring and visualising mtcars dataset statistically.

Develop Data Products course shinyapp project

My first R project exploring the mtcars dataset.

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slidify presentation for Developing Data Products project describing mtcars Explorer Shiny app

Une application Shiny pour l’exploration interactive du jeu de données mtcars. Elle propose plusieurs visualisations (nuage de points, boxplot, histogramme) et un résumé statistique scindé, accompagnés d’une documentation intégrée.

Coursera :: DataScience Specialization :: Data Products :: Final Project

Interactive Shiny dashboard for exploring the mtcars dataset, created as a course project for Coursera “Developing Data Products”. Includes a dynamic app and a reproducible pitch presentation.

A shiny app to explore variable correlation in mtcars data set

Mtcar data explorer for linear regression class

Reproducible Pitch Presentation - Explore the relation between two mtcars variables

An R project for exploring and analyzing the mtcars dataset

Exploring different linear regression techniques using the mtcars dataset in R

Description of using the mtcars data set to explore various features of knitr.

Using the mtcars and cnbc dataset, I'm exploring the hierarchical clustering technique.

Explores the use of multi-variable predictors on a regression line using the "mtcars" data set.

Analysis of the classic mtcars dataset in R — exploring fuel efficiency, horsepower, and custom performance metrics.

Visualizing the mtcars dataset using Matplotlib to explore patterns, trends, and relationships in car performance and specifications.

Interactive Shiny app for exploring mtcars data with point selection via hover, click, and brush, displaying selected points in a dynamic table.

A regression project that exploring the "mtcars" dataset, including the data diagnostic, t-test and finding a parsimony model for predicting the MPG(per gallon one mile).

This script creates a simple multivariate scatterplot using ggplot2 and the mtcars dataset to explore relationships between car weight, fuel efficiency, and cylinder count for a visual analytics assignment.

Using the mtcars dataset, I'm exploring three different types of regression: (1) Lasso; (2) Ridge ; (3) StepLR . I'm providing my recommendations on which one is the most ideal.

An R project analyzing the mtcars dataset with summary statistics (mean, median, standard deviation) and visualizations. Includes histograms for MPG & HP and a scatterplot to explore the relationship between horsepower and fuel efficiency.