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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.
End-to-end retail sales analytics workflow: Python, PostgreSQL, SQL, DAX, Power BI, and business insights.
An interactive business dashboard built during my Microsoft Excel and Power BI learning journey using a Samsung Global Sales sample dataset.
Machine learning pipeline for emotion classification using data mining, feature selection, clustering, PCA, and classification algorithms on physiological ECG data.
End-to-end machine learning application that classifies Iris flower species using a Scikit-learn pipeline with Random Forest, featuring model training, evaluation, and an interactive Streamlit dashboard.
Microsoft Excel portfolio featuring data preparation, sorting, outlier analysis, PivotTables, and data visualizations using a Bike Sales dataset.
This repository contains an Exploratory Data Analysis (EDA) project designed to practice fundamental data science skills. The goal is to clean a raw dataset, analyze underlying trends, and use data visualization to answer core business or research questions.
Python data analytics projects using Pandas, Matplotlib, Seaborn, and Jupyter Notebooks, organized in separate project folders.
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.
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 modular Python habit tracker with streak analysis, completion rates, and matplotlib visualizations.
Smart Network Traffic Analyzer built using Python, Streamlit, Pandas and Plotly for monitoring and visualizing network traffic.
A three part statistical diagnostic study of Spotify Music popularity using Multiple Linear Regression, Heteroscedasticity corrections, and influence analysis in R.
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.
Interactive Power BI dashboard analyzing internship enrollment, completion, dropout trends, mentor interactions, attendance, and departmental performance.
Power BI dashboard analyzing employee attrition by age, salary, role, and tenure
StackOverflow Java Stats - SUSTech Project of CS209A: Computer System Design and Applications A in Fall 2025 - Score: 98.5/100
Hotel Booking Analytics & Cancellation Prediction Project using Excel Dashboard and Orange Data Mining.
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