Discover My Data-Driven Innovations
Explore a collection of projects where creativity meets analytics. From predictive models to data visualization, each project showcases my journey of solving complex problems and delivering actionable insights.
Aitโ614 predictive modeling for credit approval
Explore a collection of projects where creativity meets analytics.
Ait-622:Exploring Trends in Medicare spending
This project involved a detailed analysis of the Medicare Part D Spending by Prescription dataset, focusing on identifying trends and patterns in prescription drug spending. The insights generated from the analysis aim to improve healthcare policy, reduce costs, and enhance patient outcomes.
Cs504-Building an Efficient Library Database System for Resource Management
This project focuses on designing and implementing a database management system for a public library, incorporating entities like books, members, and staff. It includes database normalization, relational schema design, and SQL query execution for efficient management of library resources and member activities.
B18-Voice Command Automation: Implementing Speech Recognition for Interactive Systems
This project focuses on developing a voice-controlled assistant using machine learning techniques for speech-to-text and text-to-speech processing. It enhances user interaction by integrating online search functionalities and commands for a range of tasks, demonstrating significant advancements in natural language processing and automation.
Stat-Churn Rate Prediction for Bank Customers
This project analyzes customer churn in the banking sector using various predictive models such as Random Forest, Logistic Regression, and Decision Trees. It identifies key factors contributing to churn, with an 86% accuracy in predicting customer behavior based on attributes like age, credit score, and account balance.
ait-580
This project analyzes the impact of climate change on temperature variations using the Global Historical Climatology Network dataset. It employs statistical methods such as linear regression and visualizations to investigate the relationship between temperature, precipitation, and climate change in U.S. cities, providing insights for ecosystem and water management.