name: "Prathab"
location: "Bengaluru <--> Coimbatore"
current_role: "Principal Software Engineer @ Informatica"
education: "B.Tech Computer Science and Engineering + PG Diploma in Data Science and Machine Learning"
alma_mater: "Amrita School of Engineering, Coimbatore + Indian Institute of Technology, Madras"
focus: "Distributed Systems, Machine Learning, General Engineering"
philosophy: "Build to understand, understand to build"
hobbies: ["Badminton", "Homelab", "Physics", "Mathematics", "Open Source"]

• 🔧 Building cloud-native microservices
• 🌐 Exploring distributed systems patterns, scalability, and fault tolerance
• 🤖 Diving deep into Machine Learning & AI
• 🏠 Setting up and managing homelab infrastructure for learning and experimentation
• 📚 Deep diving into system internals
• 💪 Maintaining fitness through badminton

Java Spring Boot Application for Apartment Management

• 🏗️ Tech: Spring Boot, JPA
• 🎯 Purpose: Comprehensive apartment management system
• ⭐ Highlights: RESTful APIs, microservices architecture, community management features

React Frontend for MyHome Application

• 🏗️ Tech: React, Material-UI
• 🎯 Purpose: Modern web interface for apartment management
• ⭐ Highlights: Responsive design, real-time updates, intuitive UX

Personal Development Environment Configuration

• 🏗️ Tech: Shell scripts, configuration files
• 🎯 Purpose: Automated development environment setup
• ⭐ Highlights: Cross-platform compatibility, one-command setup

Love building and managing homelab setups with containers, and self-hosted services. It's my playground for experimenting with distributed systems, ML workloads, and infrastructure automation.

Passionate contributor to open source projects.

Passionate badminton player who believes physical fitness enhances mental agility.

Deep fascination with physics and mathematics as the foundation of understanding our universe. Currently applying mathematical principles to machine learning.

Currently pursuing a PG Diploma in Data Science and Machine Learning from IIT Madras while exploring neural networks, deep learning, and their practical applications in real-world problems.