Attrition Data analysis

• Designed and implemented an HR attrition analysis dashboard in Tableau, highlighting key drivers of employee churn. • Utilized Python for predictive analytics, achieving an 84% accuracy rate using Logistic Regression and Random Forest models. • Delivered recommendations to senior management

US Traffic Accidents Trend Analysis and Severity Classification

The objective of this research is to analyze historical accident data to identify patterns and trends in accident occurrence, contributing factors, and potential solutions.

E-Commerce Recommendation System Using Clustering models on Visual Similarity

This project aims to improve e-commerce recommendation systems using machine learning techniques for fashion product recommendations to a dataset containing over 5000 high-definition clothing images.

Analysis of Wildlife Strikes on Civil Aviation

This project focuses on the aforementioned factors and tries to ascertain levels of contribution for each factor. This project aim is to provide in-depth analysis of dataset visualization through various types of graphs.

Bike Share Demand Prediction and Rebalancing

The project aims to address the challenges arising from the rapid growth of metropolitan areas and the increasing need for bike-sharing programs. The objective is to predict the demand for bike share using a variety of machine learning regression models.

Data - Driven Analysis of EV Charging Infrastructure for a Smart City

This project conducts a meticulous data-driven analysis, concentrating on the unique challenges and opportunities of the charging infrastructure.

House prices prediction

Analyzing house price data using machine learning models to predict house prices.

AMP-Parkinsons Disease Progression Prediction

The goal is to predict MDS-UPDR scores, which measure progression in patients with Parkinson's disease.