Join a vibrant digital realm where students explore, learn, and grow. The frontend of dmj's education initiative is a world of accessible knowledge, powered by technology.

Join a vibrant digital realm where students explore, learn, and grow. The frontend of dmj's education initiative is a world of accessible knowledge, powered by technology.

A data-driven HR analytics project analyzing employee demographics, performance metrics, salary factors, and correlations. Includes data cleaning, outlier removal, visualization, feature engineering, and multiple ML models—achieving 99%+ accuracy in salary prediction using Random Forest and XGBoost.

A data analysis project exploring 1,000 supermarket transactions using Python. Includes data cleaning, exploratory analysis, visualizations, and insights on sales, customer behavior, payment trends, and gross income across branches.

An exploratory data analysis of COVID-19 data across 225 countries, covering cases, deaths, death percentages, continent trends, correlations, and population impact. Includes visualizations with Python, Pandas, Matplotlib, and Seaborn.

A comprehensive collection of notes, assignments, and project work for the Google Cloud Platform (GCP) course at National Quemoy University.

Exploratory analysis of 18k+ electronics sales records with full data cleaning, feature engineering, and visual insights. Highlights best-selling products, revenue trends, peak purchase hours, and city-wise performance for retail decision-making.

A machine learning project analyzing advertising data (TV, Radio, Newspaper) to predict sales. Includes data cleaning, outlier removal, feature scaling, multiple regression models (Linear, Decision Tree, Random Forest, XGBoost), cross-validation, and deployment via Tkinter and Streamlit.

Exploratory data analysis of the classic mtcars dataset, examining mileage, horsepower, weight, cylinders, and performance metrics. Includes visualizations, correlations, and key insights into how car specifications impact fuel efficiency and speed.