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End-to-end Exploratory Data Analysis (EDA) project on Superstore Sales dataset including data cleaning, feature engineering, outlier handling, customer segmentation, and business insights using Python, Pandas, Matplotlib, and Seaborn.
A three part statistical diagnostic study of Spotify Music popularity using Multiple Linear Regression, Heteroscedasticity corrections, and influence analysis in R.
A data-driven deep dive into the correlation between professional stress, lifestyle habits, and sleep quality. Features Exploratory Data Analysis (EDA) and health metric visualization using Python.
Data analysis of Taylor Swift's Spotify discography using Python. Exploring correlations between track popularity, duration, and artist trends with Pandas and Seaborn
It is a technological system designed to identify & determine whether individuals within a given space or through a camera feed are wearing face masks or not. It employs computer vision algorithms, machine learning models, or deep learning techniques to analyze visual data, & detect the presence or absence of face masks on individuals faces.
This repository contains an R script for generating Circos plots to visualize accessory gene presence-absence patterns and expression levels in *Streptococcus pneumoniae* serotype 3. It compares clade I (PT8465) and clade II (ND6401) strains, highlighting differences in gene expression and adaptation.
A Python Data Science script utilizing Pandas and Matplotlib to process, aggregate, and visualize 8 months of high-intensity fitness metrics into an interactive dashboard.