Iris Flower Classification

The Iris dataset with 150 samples and four features was classified into three species using Logistic Regression, Random Forest, and Decision Tree Classifier, achieving 98% precision, enhancing botanical research accuracy.

Axon Sales Analysis

Integrated MySQL with Power BI for data cleansing and transformation, developed a dynamic dashboard boosting sales forecasting accuracy by 30%, addressed missing values, formatted data, and created measures, enabling data-driven decisions with real-time analytics on sales, revenue, and profit.

Texture Tales case study

Analyzed 10,000+ Texture Tales Clothing Company records using MySQL, generating a financial report with 15+ SQL functions. Enhanced data validity by 20%, forecasted demand, and identified growth opportunities, projecting a 25% increase in profitability through improved sales performance.

Weather Dataset Analysis

Conducted exploratory data analysis on a time-series weather dataset, analyzing variables like temperature, humidity, wind speed, and pressure. Explored correlations to derive insights for climate research and decision-making, aiding in understanding historical patterns and predicting future climate

Credit Card Approval Prediction

In this credit card approval prediction project, Python and its libraries were utilized for data preprocessing, feature engineering, and model training. Features such as income, credit score, and employment status were analyzed using algorithms like logistic regression or decision trees.