Kidney Cancer Analysis using R

The objective of this project is to identify the relationships between various medical factors and predicting the neoplasm status of the patient. Predictive models like Logistic regression, random forest and decision trees were employed. The Logistic regression model emerged as the winner.

LinkedIn Profile Classification using NLP in Python

The objective of this project is to optimize candidate selection by integrating the best classification model with a chatbot for user interaction. I leveraged scikit-learn to build and assess various classifier models. The random forest model achieved the highest accuracy at 82% on test data.

Forecasting Energy Demand - SAS

The objective of this project is to identify the optimal forecasting model for a 2-year energy demand forecast using data from American Electric Power. Various models were employed. The X11 decomposition model emerged as the winner with a MAPE accuracy of 4.17%.

Cerulean Bee using MSAccess

The objective of the project was to develop a fully-functional relational database for Cerulean Bee, an Art Company. Utilized ERDPlus to construct a logical model and implemented the relational database along with forms and reports using Microsoft Access. Designed OLAP cubes to analyze KPIs.

House rent vs buy - spreadsheet modeling

The objective of this project is to create an Excel-based decision-making tool that will consider the costs of buying a house versus renting a similar one and provide a decision based on the current market situation.

Breast Cancer Analysis using SAS

The goal is to comprehend the relationships between variables, analyze, and identify the best predictive model for determining the status (Alive or Dead) of new patients. The CART model emerged as the winner, achieving an accuracy of 86.02% and a specificity of 96.22%.

Alliance Sales using SSIS,SSRS,PowerBI

The aim of the project was to establish a data warehouse solution for weekly sales transactional data. Developed an ETL process to generate fact and dimension tables from Excel files. Designed reports to address high-level managerial inquiries and analyze key performance indicators (KPIs).

Amusement Park Simulation using Simio

The goal of this project is to identify the optimal proportion of fast pass customers that the manager at an amusement park can sell on a day by retaining the satisfaction of both the regular and fast pass customers. Designed a Simio model with separate routes for regular and fast pass customers.