ChurnSense-AI: End-to-end telecom churn prediction system with XGBoost, SHAP explainability, SQL analytics, Power BI dashboards, and customer risk intelligence.

End-to-end ML project that classifies emails as Spam or Not Spam using NLP, TF-IDF, Logistic Regression and Streamlit.

End-to-End MLOps Pipeline: Train, track, containerize, and deploy ML models via FastAPI REST API with automated CI/CD on Render.

⚽ A machine learning project that predicts the 2026 FIFA World Cup using FIFA rankings, historical match results, Poisson regression, and Monte Carlo simulation.

An end-to-end Machine Learning application that predicts the likelihood of heart disease based on patient medical attributes. The project demonstrates the complete ML workflow, including data preprocessing, exploratory data analysis, model training, evaluation, and deployment through a user-friendly Flask web application.

A deep learning project that predicts a student's **chance of admission** to a graduate program based on academic and profile features.

Java program that plots random points in a 3D space and assigns their (x, y, z) coordinates their respective [R, G, B] values and displays them in the plot with their RGB color.

AI-powered IPL analytics platform with match prediction, team/player insights, and Explainable AI (XAI) — built with Flask, scikit-learn & Plotly.

Machine Learning project for predicting customer purchase behavior using a Decision Tree Classifier on the Bank Marketing Dataset with data preprocessing, feature importance analysis, confusion matrix visualization, and decision tree interpretation.

Fine-tuned DistilBERT for political misinformation classification with cross-dataset evaluation across LIAR and Fakeddit benchmarks, compared against Logistic Regression, Naive Bayes, and SVM baselines.