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  • Hyderabad
  • 04:12 (UTC +05:30)

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itzzdev09/README.md

⚡ Devraj Pal (itzzdev09)

Full-Stack Software Engineer • Machine Learning Practitioner • Cloud & DevOps

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🖥️ $ whoami

devraj@workstation:~$ neofetch --profile
  OS: Linux / Windows Subsystem for Linux (WSL2)
  Kernel: Clean Architecture & Modular Microservices
  Uptime: 24/7 Problem Solver & Lifelong Learner
  
  Current Roles:
    - 🚀 Full-Stack Architect @ PrepArsenal (Next.js 15, Supabase, Python, LLM RAG)
    - 🔬 ML Systems Engineer (Explainable AI, PyTorch, CatBoost, SHAP)
  
  Tech Stack:
    - Frontend: Next.js 15, React 19, TypeScript, Tailwind CSS, Responsive UI
    - Backend: Node.js, Express, Python (Django, Flask, FastAPI), RESTful & GraphQL APIs
    - ML / Data: PyTorch, CatBoost, Scikit-Learn, Pandas, NumPy, Kafka, Redis
    - Cloud / DevOps: Docker, Kubernetes, Microsoft Azure, Linux, CI/CD Actions
  
  Engineering Core:
    - "Simplicity over complexity. Production-grade resilience over quick hacks."

🚀 Interactive Tech Stack

Languages & Core Technologies

Languages

Frameworks, Libraries & Full-Stack

Frameworks

Machine Learning, Data & Caching

Data & ML

Cloud, DevOps & Engineering Tools

DevOps

🏆 Featured Flagship Repositories

🎯 PrepArsenal

AI-Powered Exam Preparation & Adaptive Testing Engine

  • Ingested 25,800+ deterministic PYQs across 9 high-stakes competitive exams.
  • Item Response Theory (IRT) adaptive practice algorithms & ML trend forecasting.
  • Built with Next.js 15, Supabase, TypeScript, and Python.

🛡️ XAI-PyTorch-IDS

Explainable AI Network Intrusion Detection System

  • Multi-class intrusion detection on imbalanced datasets using CatBoost with GPU acceleration.
  • Model interpretability using SHAP feature importance & stratified downsampling.
  • Built with PyTorch, CatBoost, SHAP, and Python.

🏡 Flat-AI

Smart Real-Estate Marketplace & Valuation Platform

  • End-to-end MERN platform for property discovery with intelligent recommendation engine.
  • Integrated Django ML microservice for automated real-time property price estimation.
  • Built with React, Node.js, Express, Django, and MongoDB.

📈 PrismPrice

Dynamic Pricing Decision-Support Engine

  • Real-time price elasticity modeling, demand curve estimation, and customer retention metrics.
  • Automated price governance and causal revenue optimization.
  • Built with Python, Kafka, Scikit-Learn, and Pandas.

📊 System Architecture & Engineering Principles

  ┌─────────────────┐       ┌─────────────────┐       ┌─────────────────┐
  │  Next.js / SSR  │ ────> │ Node/Express API│ ────> │ PostgreSQL / DB │
  │ React & Tailwind│       │  Auth & Routing │       │ Supabase & RLS  │
  └─────────────────┘       └─────────────────┘       └─────────────────┘
           │                         │                         │
           ▼                         ▼                         ▼
  ┌─────────────────┐       ┌─────────────────┐       ┌─────────────────┐
  │ PyTorch / ML Svc│ <───> │ Redis & Caching │ <───> │ Docker & K8s CI │
  │  XAI & CatBoost │       │ Real-Time Queue │       │ Azure Deployment│
  └─────────────────┘       └─────────────────┘       └─────────────────┘
  • 🧱 Architectural Cleanliness: Modular separation of concerns, DRY principles, type safety with TypeScript & Python type annotations.
  • ⚡ Performance First: Edge caching, async database concurrency, vector indexing, and minimal bundle overhead.
  • 🔒 Security Mindset: Strict Row-Level Security (RLS), JWT verification, input sanitization, and automated test suites.

📬 Connect & Collaborate

Let's collaborate on impactful engineering projects, full-stack systems, or machine learning infrastructure!

LinkedIn Email GitHub


Crafted with engineering precision by Devraj Pal (itzzdev09) • Powered by Open Source

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