Project Cabinet: My Coding Projects Showcase

Project Cabinet is an interactive portfolio showcasing my coding projects through visually engaging cards. Featuring responsive design, advanced filtering, and sorting, it offers a dynamic and organized presentation of my work, highlighting my technical skills and project expertise in a user-friendly format.

    Tech Stack:
  • React
  • Tailwind CSS
  • Next.js
  • Typescript
  • Javascript
  • Sofware Development
  • Web Development

ELT Pipeline Development and Deployment with AirFlow

Configured a Snowflake environment with 5 warehouses, 10 roles, and 3 schemas, ensuring robust RBAC. Implemented 8 dbt models for staging and fact tables, optimizing transformations. Orchestrated and automated the ELT pipeline on Apache Airflow, enabling efficient and reliable data workflows.

    Tech Stack:
  • dbt
  • Snowflake
  • Airflow
  • SQL
  • Data Science
  • Data Analytics

Full Stack Recipe Sharing Platform

Developed a recipe-sharing platform using React, Tailwind CSS, and Django. Deployed the frontend on AWS S3 with CloudFront, and the backend on EC2 with Nginx and Gunicorn. Managed PostgreSQL database migrations and schema updates, and enhanced security by configuring a custom private subnet using AWS VPC.

    Tech Stack:
  • React
  • EC2
  • S3
  • CloudFront
  • SQL
  • Django
  • Web Development
  • Sofware Development

Data Analysis and Visualization of World Development Indicators

Analyzed the World Development Indicators dataset for 100+ countries using Python, revealing trends in GDP and clean fuel access. Reduced dataset size by 15%, improving analysis efficiency. Created visualizations that enhanced insights into global development over 50 years.

    Tech Stack:
  • Python
  • matplotlib
  • Pandas
  • Data Analytics

Predictive Analysis and Insights on NBA Playoff Outcomes

Conducted data preprocessing and analysis on NBA datasets (2014-2023) using R (tidyverse, dplyr), generating visualizations with ggplot2 and plotly. Developed logistic and linear regression models to predict NBA playoff outcomes, achieving 75% accuracy in forecasting series winners and the number of games.

    Tech Stack:
  • R
  • tidyverse
  • ggplot2
  • caret
  • plotly
  • Data Science
  • Machine Learning
  • Data Analytics

AI-Driven GitHub Issue Classification System

Built a machine learning model with 85% accuracy for classifying GitHub issues using Logistic Regression and PySpark on Databricks (GCP Compute). Developed a React-based frontend for a user-friendly interface, enabling real-time issue classification and predictions.

    Tech Stack:
  • PySpark
  • MLlib
  • Databricks
  • GCP
  • Web Development
  • Sofware Development
  • Machine Learning
  • Artificial Intelligence