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federicobrancasi/README.md

👋 Hey, I'm Federico - Let's Code the Future Together!

Greetings from my coding corner! I'm Federico, an enthusiastic explorer in the expansive realm of computer science. Currently, I'm immersed in the captivating journey of pursuing a Double M.S. in Computer Science at the University of Trento and Eötvös Loránd University in Budapest, infusing a fintech flavor into my studies. I'm on the lookout for like-minded visionaries eager to shape the future alongside me.

🌐 Let's Connect and Collaborate

🛠️ Peek into My Coding World

Here are some carefully selected projects I have on GitHub:

  1. Enhanced File Explorer for Chrome

    • Quick Take: Improves Chrome's file explorer when browsing local files, compatible with all the Chromium-based browsers.
    • Key Features:
      • Enhanced browsing experience for local files
      • Over 600 daily users and 3000+ installations
    • Tech Stack: JavaScript, Chrome Extension API
    • GitHub: Explore Project
  2. Test-Time Adaptation for Image Classification

    • Quick Take: Explores innovative approaches to enhance the robustness of pre-trained neural networks for image classification when faced with out-of-distribution test data.
    • Key Features: Implements Test-Time Adaptation techniques, leverages Vision-Language Models, and explores prompt engineering and learning.
    • Tech Stack: Python, PyTorch, AWS
    • GitHub: Explore Project
  3. Mathematics for Machine Learning

    • Snapshot: Detailed notes and exercises for the "Mathematics for Machine Learning" specialization at Imperial College London
    • Key Contents:
      • Cheatsheets on Linear Algebra, Multivariate Calculus, and Principal Component Analysis
      • Python labs including projects like PageRank algorithm implementation and Neural Network training
    • Tech Stack: Python, Jupyter Notebooks
    • GitHub: Explore Project
  4. Deep Learning Course Book

    • Snapshot: A comprehensive LaTeX-based book for the Deep Learning course at the University of Trento, designed to assist future students.
    • Highlights: Custom illustrations created using the TikZ library, covering key concepts and techniques in deep learning.
    • Tech Stack: LaTeX, TikZ
    • GitHub: Explore Project

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  1. Deep-Learning Deep-Learning Public

    Comprehensive LaTeX-based deep learning guide with custom TikZ illustrations

    TeX

  2. Mathematics Mathematics Public

    Detailed notes and exercises for the "Mathematics for Machine Learning" specialization of Imperial College London.

    Jupyter Notebook

  3. Enhanced-File-Explorer-for-Chrome Enhanced-File-Explorer-for-Chrome Public

    Improves chrome's file explorer when browsing local files.

    CSS 2

  4. Test-Time-Adaptation-for-Image-Classification Test-Time-Adaptation-for-Image-Classification Public

    Enhances neural network robustness for image classification

    Jupyter Notebook 1 1