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Tresssco/README.md

Hi, I'm Jorge 👋

My background combines hands-on industrial systems development with data analysis and machine learning. After working in automation, I am currently expanding my skill set towards AI and Big Data, aiming to apply these technologies in real-world environments where data and processes intersect.

I focus on building practical solutions beyond academic settings, developing projects that integrate machine learning models with real-world problems — especially in industrial contexts.

🤖 AI & Data Science

Python scikit-learn PyTorch Jupyter Pandas NumPy

🗄️ Big Data & Systems

Linux HDFS Apache Hive Sqoop MariaDB

🏭 Industrial Automation

TIA Portal ABB AVEVA Indusoft OMRON

📂 Featured Projects

Project Description
Agente-Inteligente-RPS Model-based reactive agent (Russell & Norvig)
Supervised-Learning-Credit-Prediction Supervised models applied to real financial data
Unsupervised-Learning-Country-Clustering K-Means + PCA with geographic visualization
Simulated-Annealing Optimization using simulated annealing
Algoritmos-de-Busquedas BFS, DFS, UCS and A* implementations

🚀 Current Focus

  • Building real-world AI projects
  • Deepening knowledge in Big Data and distributed systems
  • Exploring AI applications in industrial environments

Popular repositories Loading

  1. Agente-Inteligente-RPS Agente-Inteligente-RPS Public

    Implementación en Python de un agente reactivo basado en modelo para Piedra-Papel-Tijera, con análisis del entorno de tareas y extensión a Lizard-Spock. Basado en Russell & Norvig.

    Python 1

  2. Algoritmos-de-Busquedas Algoritmos-de-Busquedas Public

    Resolución de ejercicios de búsqueda en anchura, profundidad, coste uniforme y A* con distancia Manhattan. Incluye análisis de frontera, nodos explorados y árboles de búsqueda.

  3. Simulated-Annealing Simulated-Annealing Public

    USA radio stations: Set covering problem

    Python

  4. Supervised-Learning-Credit-Prediction Supervised-Learning-Credit-Prediction Public

    Supervised learning project applying multiple classification algorithms (KNN, Logistic Regression, Decision Tree, Random Forest, SVM) to predict whether a client will subscribe to a bank credit, ba…

    Jupyter Notebook

  5. Unsupervised-Learning-Country-Clustering Unsupervised-Learning-Country-Clustering Public

    Aplicación de K-Means y PCA sobre un dataset de 167 países para identificar grupos según indicadores socioeconómicos y de salud. Incluye visualización geográfica con GeoPandas.

    Jupyter Notebook

  6. Tresssco Tresssco Public