Earnomly is a modern fintech-styled platform that uses machine learning (Random Forest, Logistic Regression) to analyze socioeconomic factors and predict income levels using the UCI Adult dataset.

An analysis of the factors that explain real estate prices in Tokyo.

This project leverages machine learning techniques to analyze online retail data through customer segmentation. It uses KMeans clustering to identify key customer groups and proposes tailored business strategies based on their purchasing behaviors.

Data Analysis with Python Projects leverage the power of Python's extensive libraries and tools to explore, visualize, and draw insights from datasets

End-to-End Machine Learning web app featuring automated CI/CD pipelines and cloud deployment on AWS

PacketWatch – Advanced Network Intrusion Detection using Machine Learning. Real-time monitoring, anomaly detection, and secure API deployment with FastAPI

FailSafe: Autonomous Deployment Risk Engine

SegmentStream Test App

This project predicts London’s daily temperature using machine learning. It follows a structured ML workflow with EDA, data cleaning, model training, and experiment tracking with MLflow.

AL/ML Internship Tasks

Machine Learning