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Achievement: Galaxy BrainAchievement: YOLOAchievement: QuickdrawAchievement: Pull Shark

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Pranee-2212/README.md

Hi there, I'm

Praneet Vadakkancherry Ganesh Kumar! 👋

Backend Developer | Cloud Enthusiast | AI Integrator

Based in Ilmenau, Germany 🇩🇪

LinkedIn GitHub

👨‍💻 About Me

  • 🎓 Pursuing my Master's in Research in Computer and System Engineering at TU Ilmenau.
  • 💻 Passionate about Backend Development, Cloud Infrastructure, and AI Workflows.
  • 🤖 Actively experimenting with local LLMs, AI agents, and automating data pipelines.
  • 🏋️‍♂️ When I'm not coding or managing personal servers, you can usually find me hitting the gym, sketching digital art, or running a DEX build in Elden Ring.

🛠️ Tech Stack & Skills

☁️ Cloud & Infrastructure (Focus)

Docker Kubernetes Git Linux Ubuntu Fedora Mint

💻 Languages & Web Development

Python JavaScript Node.js Flask MySQL Web Development

🧠 AI Integration & Prompt Engineering

AI Integration Prompt Engineering

🤝 Soft Skills

Problem Solving | Technical Communication | Analytical Thinking | Project Management

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  1. cloud_project-_tu_ilmenau cloud_project-_tu_ilmenau Public

    An image classification API built with FastAPI and PyTorch, deployed on a local Kubernetes cluster (Minikube) using a decoupled Least-Connections Load Balancer, a Custom Dynamic Autoscaler, and Pro…

    Python

  2. bare-metal-to-cloud bare-metal-to-cloud Public

    A documented journey of building a secure home lab from scratch — SSH hardening, NAS setup, and everything that broke along the way.

  3. Distributed-Asset-Health-Monitor Distributed-Asset-Health-Monitor Public

    A microservices-based uptime monitoring system built with Python (Flask) and MySQL. Features a decoupled architecture with a dedicated "Watcher" service for asset management and a "Logger" service …

    Python

  4. Emotion-Based-movie-recommendation Emotion-Based-movie-recommendation Public

    web app built with Flask that analyzes user input text to detect emotions and recommends movies tailored to the detected emotion using a machine learning model.

    Jupyter Notebook