A comprehensive R-based data analysis project that examines housing rental patterns across multiple cities, utilizing statistical methods and visualization techniques to analyze 4,746 properties' data points including rent prices, locations, and amenities. The project employs various R libraries to clean, process, and visualize rental market trends

A jupyter notebook approach using pythong to track and estimate the rotation period of an asteroid.

Student Performance Analysis This project analyzes a dataset of 10,000 student records to uncover insights into academic performance. Using Python and Pandas, it processes and visualizes key trends related to students' grades, study habits, and other influencing factors.

This project is a Natural Language Processing (NLP) initiative that performs sentiment analysis on IMDB movie reviews.

Segment Sphere is a customer segmentation tool using RFM analysis to group customers based on recency, frequency, and monetary value. It processes e-commerce data, provides actionable insights, and visualizes results with interactive charts. Ideal for understanding customer behaviour and supporting data-driven decisions.

English to SQL, English as Query Language

🎢 IaaS visual editor to create & deploy data processing pipelines - python, rmq, react, meteorjs

This project focuses on predicting employee attrition using machine learning techniques. It analyzes factors influencing employee turnover, such as job satisfaction, work environment, and compensation. By leveraging data preprocessing, feature selection, and classification models, the project provides insights for retaining valuable talents.

This Project aims to implement a **Hadoop MapReduce job in Pseudo-Distributed Mode** to determine the **feistiest Pokémon** based on their **type**. The job processes the Pokémon dataset (`pokemon.csv`) and outputs a CSV file containing Pokémon **type1, type2, name, and feistiness score**.