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Achievement: Pull Shark

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joao-viterbo-vieira/README.md

About Me

I am an AI and Data Science student pursuing an MSc in Data Science and Engineering at FEUP. With a foundation in Industrial Engineering and Management, I am passionate about leveraging data-driven solutions and AI technologies to address complex problems. My focus lies in studying and developing advanced agent-based solutions as a stepping stone toward Artificial Superintelligence (ASI). I am deeply committed to staying at the forefront of AI advancements, continuously learning from leading industries, markets, top researchers, and the latest academic papers from renowned institutions such as Stanford, MIT, Google, META, OpenAI, Anthropic, and others.

🔭 Current Focus

  • AI Advancements: Learning cutting-edge AI from top industries, researchers, and papers, via institutions like Stanford, MIT, META, OpenAI, Google etc.
  • AI Applications & Implementation
  • Intelligent Systems Development (Agentic AI)
  • Data Science & Analytics
  • Machine Learning Algorithms
  • Statistical Analysis
  • Data Visualization and Analytics Dashboards
  • Process Optimization and Project Management

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  1. Bird-Call-Feature-Extraction-and-Clustering Bird-Call-Feature-Extraction-and-Clustering Public

    Extracts time and frequency domain features from bird call audio (e.g., ZCR, spectral features, MFCCs) and applies K-Means clustering to group calls of four bird species.

    Jupyter Notebook

  2. Data-Visualisation-and-Preparation-in-R Data-Visualisation-and-Preparation-in-R Public

    This repository uses R to analyze renewable energy adoption in Europe. It cleans and merges Eurostat data on energy consumption, renewables, and population, and then creates insightful visualizatio…

    R

  3. Enhanced-Naive-Bayes-Classifiers-with-Discretization-and-KDE Enhanced-Naive-Bayes-Classifiers-with-Discretization-and-KDE Public

    Enhanced Naive Bayes classifiers using discretization and KDE for improved accuracy and robustness, scoring 19.2/20 in an MSc Data Science and Engineering ML course.

    Jupyter Notebook

  4. ERP-MES ERP-MES Public

    ERP-MES: A Pascal-based system integrating ERP and MES functions—production planning, inventory, quality control, and real-time monitoring—with a PostgreSQL database.

    Pascal

  5. Optimizing-Warehouse-Location-MIPvs.CP Optimizing-Warehouse-Location-MIPvs.CP Public

    Optimization Models for the Warehouse Location Problem: A Comparative Study of MIP and CP Approaches

    Python 1

  6. Statistical-Analysis-of-Wildfires-in-Portugal Statistical-Analysis-of-Wildfires-in-Portugal Public

    This study employs statistical methods, including hypothesis testing, to analyze wildfire patterns, trends, and factors influencing wildfire occurrences in Portugal. (MSc Data Science and Engineering)

    Jupyter Notebook