Projects

A collection of my recent work in software development and data science.

Currently in Progress

Learning Management System

A modern Learning Management System enabling course creation, student progress tracking, and interactive learning experiences with real-time assessment capabilities.

Next.js
TypeScript
Prisma
PostgreSQL
AWS S3
Progress: 0%
zyumn.ai

AI-powered trading platform with real-time market analysis, strategy backtesting, and performance analytics. Uses machine learning for sentiment analysis and automated technical trading signals.

Next.js
Go
Python
Kafka
TimescaleDB
Docker
Kubernetes
LangChain
Progress: 0%

Completed Projects

Hirestack

A scalable, serverless job aggregation platform that processes real-time data from multiple job boards and provides intelligent job recommendations using machine learning.

Python
Django
Next.js
AWS
DynamoDB
Machine Learning

Type

Full-Stack Web Application

Key Achievements

  • Reduced infrastructure costs by 40% through serverless architecture
  • Improved job matching accuracy by 25% using ML algorithms
  • Scaled to handle 1M+ daily active users

Details

  • Implemented serverless architecture using AWS Lambda and API Gateway
  • Designed and optimized DynamoDB schema for efficient querying
  • Developed machine learning models for personalized job recommendations
  • Integrated with multiple job board APIs for real-time data aggregation
  • Implemented user authentication and profile management features
RetailPulse

An IoT-based People Counter application using computer vision for accurate real-time customer tracking in retail environments, providing actionable insights for store optimization.

Python
OpenCV
FastAPI
Docker
PyTorch
IoT

Type

Computer Vision & IoT Application

Key Achievements

  • Achieved 95% accuracy in people counting
  • Reduced manual counting labor by 100%
  • Provided actionable insights leading to 15% increase in store efficiency

Details

  • Developed computer vision algorithms for accurate people counting
  • Implemented real-time data processing pipeline using FastAPI
  • Designed and built responsive dashboard for visualizing foot traffic data
  • Integrated with IoT devices for seamless data collection
  • Containerized application using Docker for easy deployment
Mood of Music

A web application that generates personalized Spotify playlists from environment images using AI for mood detection and song recommendations

Python
Flask
PyTorch
Spotify API
OpenAI API
PostgreSQL
Docker
Render.com

Type

AI/ML Web Application

Key Achievements

  • Created dual recommendation system using both image analysis and user's top artists
  • Implemented containerized deployment with Docker supporting both PostgreSQL and MySQL
  • Developed responsive web interface for seamless playlist embedding and playback

Details

  • Implemented image analysis using PyTorch to extract emotional parameters from uploaded images
  • Integrated OpenAI API for image description and playlist generation based on detected moods
  • Developed Spotify API integration for playlist creation and management
  • Built user authentication system with Spotify OAuth
  • Implemented database storage for user accounts and playlist details using PostgreSQL