My Projects & Case Studies

🛡️ Privacy-Preserving Vertical Federated Learning

Designed a heart disease prediction framework using Vertical Federated Learning integrated with Zero Knowledge Proof and Differential Privacy.

Federated Learning, ZKP, DP, Logistic Regression

🧠 Multi-Category Image Classification (CNN)

Built a CNN model with skip connections for classifying multiple image categories. Analyzed performance across different architectures.

Python, Keras, CNN, Deep Learning

🧪 Regensburg Pediatric Appendicitis Multi-Class Model

Developed a machine learning model to predict Diagnosis, Management, and Severity simultaneously using a multi-output classifier on the Regensburg Pediatric Appendicitis dataset.

Random Forest, XGBoost, VotingClassifer, Multi-Output Classification, Scikit-learn

📊 Descriptive Analysis of Wrangled Data

Cleaned, visualized, and statistically analyzed customer and sales data. Focused on encoding techniques, handling missing values, and deriving insights.

Pandas, Matplotlib, Seaborn, EDA

🎵 Music Genre Classification

Trained models to predict music genres and listener moods using audio features like pitch, tempo, and rhythm.

Random Forest, SVM, Neural Networks

📞 Telecom Churn Prediction

Built churn models using customer behavior data to identify high-risk customers and key churn indicators.

Logistic Regression, Scikit-learn, Pandas

💳 Credit Risk Analysis

Analyzed loan dataset to identify key risk factors and customer trends. Visualized insights to support credit decision-making.

Python, Data Analysis, Visualization

✈️ NYC Flight Dataset Analysis

Performed EDA and regression analysis on NYC flight data using R. Studied impact of weather and delays with time series techniques.

R, ggplot2, dplyr, Time Series