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Juan-qwerty/README.md

πŸ‘‹ Hi, I'm Juan Esteban Fuentes Rojas

πŸŽ“ Systems and Computer Engineering student at the University of Cundinamarca, passionate about transforming data into strategic decisions through machine learning, data analysis, and web development.

πŸ’‘ I’m currently focused on designing and deploying systems powered by LLMs and RAG for cloud environments, especially Google Cloud Platform.


πŸš€ Technical Stack

Languages: Python, JavaScript, SQL, MATLAB
Web Development: HTML, CSS, React, .NET
Databases: MySQL, SQLite, PostgreSQL
Data Science: Power BI, Pandas, NumPy, Scikit-learn, Matplotlib
DevOps & Tools: Git, GitHub, VS Code, Google Cloud Platform


🧠 Currently Exploring

  • Cloud deployment with AWS and Google Cloud
  • CI/CD pipelines and DevOps best practices
  • Generative AI and model optimization for real-time applications

πŸ”­ Featured Projects

  • 🌿 Water Stress Detection System β€” Developed the full frontend and dashboards for a real-time agricultural monitoring system.
    Recognized internationally for innovation in applied sciences and engineering.
    Tech: HTML, CSS, JavaScript, .NET, Python

  • πŸ¦‹ Butterfly Classifier β€” Built a neural network image classifier in MATLAB with over 90% accuracy.

  • πŸ€– YOLOv8 Model Manager β€” Created a Python interface to download and manage YOLOv8 models for object detection.

  • πŸ“š Inclusive Educational Software β€” Collaborated on the development of Braille learning software, winner of a social innovation award.


πŸ“« Let's Connect!

πŸ“§ Email: ing.fuentesjuan@gmail.com
πŸ’» GitHub: Juan-qwerty
πŸ”— LinkedIn: Jefr


⭐ β€œTransforming data into knowledge, and knowledge into impactful solutions.”

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  1. Machine-Learning Machine-Learning Public

    Este es un repositorio para evaluar distintos algoritmos de machine learning.

    Python

  2. RFGRONA/ArandanoIRTSoftware RFGRONA/ArandanoIRTSoftware Public

    C#

  3. vans13/AI-Models-Lab vans13/AI-Models-Lab Public template

    Here lies a neural network of the backpropagation type. This is divided into two sections: a class with the logic of the network; and a script with an interface to modify the training of the network.

    MATLAB