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TGMAPA/README.md

Hi there, I'm Miguel Pérez 👋

B.S. in Computer Science | AI & Intelligent Systems | Network Infrastructure & Security

I am a Computer Science student at Tecnológico de Monterrey with a strong interest in Artificial Intelligence, Machine Learning, Computer Vision, and Network Infrastructure.

Throughout my academic and personal projects, I have worked on multiple implementations involving applied AI, deep learning models, machine learning pipelines, and computer vision systems. I am also passionate about network architecture, cybersecurity, and distributed systems.

Beyond technology, I am also a musician and music enthusiast 🎶, playing guitar 🎸, bass 🎸, and drums 🥁.


🚀 Technical Skills

Programming

Python Java C++

Web & Development

HTML

Networking & Infrastructure

Cisco

Areas of Interest

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Network Infrastructure
  • Network Security
  • Distributed Systems
  • Applied AI Research

🧠 Projects

I have developed multiple projects focused on:

  • Applied Artificial Intelligence systems
  • Computer Vision applications
  • Machine Learning models and experimentation
  • Deep Learning implementations
  • Network architecture and infrastructure design
  • Personal homelab environments for infrastructure experimentation

Many of these projects are available in my repositories.

I am an active developer in the open source community

GitHub stats


🌐 Connect with me

LinkedIn


📫 Contact

Email


Always interested in collaborating on projects related to AI, intelligent systems, and advanced computing infrastructure.

Pinned Loading

  1. AI-pico-banana-project AI-pico-banana-project Public

    A full-stack system for Denoising Diffusion Probabilistic Models (DDPM) featuring dynamic model selection, web-based inference, and comprehensive model training capabilities.

    Jupyter Notebook 1 1

  2. CIC-IDS2017_ML_Analysis CIC-IDS2017_ML_Analysis Public

    Evaluación Comparativa de Modelos de Aprendizaje Automático para la Clasificación de Tráfico de Red utilizando Redes Neuronales Densas y Regresión Logística Multiclase sobre CIC-IDS2017

    Jupyter Notebook 1

  3. ClassicNeuralNets-AssociativeMemory ClassicNeuralNets-AssociativeMemory Public

    Implementación y análisis de redes neuronales asociativas clásicas (Hopfield, LAM y BAM) en Python. El proyecto evalúa la capacidad de estas arquitecturas para memorizar y recuperar patrones bajo c…

    Jupyter Notebook

  4. LZW LZW Public

    This is a 12 bits LZW Compression C program.

    C 1

  5. Thales-Callidus Thales-Callidus Public

    Este proyecto presenta un modelo de aprendizaje profundo y una plataforma de visualización interactiva para apoyar la toma de decisiones estratégicas en temas de seguridad pública en la Ciudad de M…

    Jupyter Notebook 1 2

  6. ML-LogisticRegression-Regularized ML-LogisticRegression-Regularized Public

    Implementación manual de regresión logística regularizada en Python, con gradiente descendente y mapeo polinomial de características. Incluye análisis del impacto de la regularización (λ) en overfi…

    Python 1