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ai-mg/README.md

Hi , I'm Manu Gupta

AI Engineer | Data Scientist | Full Stack Developer

LinkedIn GitHub Google Scholar Gmail

🚀 About Me

AI Engineer and Full Stack Developer with a strong foundation in computational modeling and data analysis. Leveraging my PhD experience in computational Astrophysics and analyzing space mission data, I now apply those analytical and programming skills to AI/ML and web development challenges. I love tackling complex problems and creating innovative solutions that make a difference.

  • 📖 Currently working as a Postdoctoral Researcher in AI, specializing in Computer Vision and Audio-Based Anomaly Detection Systems
  • 🤖 Pursuing: Master's in AI at Johannes Kepler University
  • 👨‍🏫 Teaching: Data Analysis at FH JOANNEUM Graz
  • 📝 Writing about: Data Science and Machine Learning on HackMD, GitHub
  • 🎯 Focus areas: Machine Learning, Data Science, Full Stack Development

💻 Technical Stack

Languages

Python JavaScript TypeScript PHP SQL C R MATLAB

AI/ML & Data Science

TensorFlow PyTorch Scikit-learn OpenCV Pandas NumPy Matplotlib Seaborn Altair

Full Stack Development

Svelte Shadcn HTML5 CSS3 Tailwind

Tools & Platforms

Git SQLite Docker Linux

🎯 Featured Projects

1. WortWizard

  • AI-powered language learning platform
  • Tech Stack: Svelte, Shadcn UI, Tailwind CSS, Claude API, SQL
  • Features:
    • AI-driven mnemonic generation
    • Wordlists on standard German and regional dialects
    • Responsive UI with modern design
    • Claude API integration

2. Solar Flare Modeling

  • Studied the Physics behind solar flares through 3D computational modeling in C and Python.
  • Conducted in-depth analysis using NASA/ESA space mission data on the Sun
  • Implemented parallel computing techniques using BASH and SGE scripts
  • Tech Stack: C, C shell, BASH, Python, NumPy, Scipy, Pandas, OpenCV, Scikit-image, Parallel Computing
  • Publications: Paper 1, Paper 2, Paper 3

💡 Recent Blog Posts

  1. Data Analysis with Python
  2. Theoretical Concepts of Machine Learning
  3. Machine Learning Supervised and Unsupervised
  4. LSTM and Recurrent Neural Networks
  5. Recommender Systems
  6. Creating Python Packages on GitHub: A Practical Guide

Profile views

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  1. AI-Notes-and-Blogs AI-Notes-and-Blogs Public

    My articles on AI topics including Theoretical Concepts, Supervised and Unsupervised Learning, and Recurrent Neural Networks. See latest blogs on https://hackmd.io/@m-g

    1

  2. create_your_own_python_package create_your_own_python_package Public

    Guide for creating Python packages on GitHub

  3. Data-Analysis-Tutorials-Python-Jupyter Data-Analysis-Tutorials-Python-Jupyter Public

    Tutorials for Data Visualization and Analysis using Python and its libraries including Numpy, Pandas, Matplotlib, Seaborn, and Altair. Additionally, instructions on how to set up Jupyter notebook a…

    Jupyter Notebook 2

  4. Recommender_Systems Recommender_Systems Public

    This project includes implementations of SVD, ItemKNN, Random, and Popularity-based recommenders to recommend songs to users based on their interaction history and demographic data.

    Jupyter Notebook

  5. stability_analysis stability_analysis Public

    A Python package for analyzing the stability of solar magnetic fields (part of my PhD project).

    Python

  6. youtube_audio_downloader youtube_audio_downloader Public

    Downloads Creative Commons–licensed YouTube audio and metadata

    Python