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carlosmorenocc/README.md

Hi! I'm Carlos Moreno 👋

Data Science & Engineering student based in Guadalajara, Mexico. 🇲🇽

I enjoy building clean data pipelines, applying machine learning, and turning data into insights people can actually use.

I’m especially interested in impact-driven projects, where data connects with real decisions from sports and mobility to geospatial and public data.

👨‍💻 About Me

  • 🎓 B.Sc. in Data Science Engineering (8th semester) at ITESO
  • 📤 Data Science Intern at Hewlett Packard Enterprise
  • 📉 Volunteer as member of the Data Science & Engineering Student Society (2025–2026)
  • 🌎 Native Spanish speaker, advanced English

I like working end-to-end: from data ingestion and cleaning, to modeling, and finally visualization through dashboards or interactive maps.

🔍 What I Work On

  • Applied Machine Learning (classification & regression)
  • Data cleaning, normalization & ETL pipelines
  • Geospatial analysis & interactive mapping
  • Sports analytics & performance data
  • Data-driven decision making
  • NLP fundamentals (tokenization, preprocessing)

🏟️ Sports & Data

Before writing code, sports — especially baseball — taught me how to think in patterns, preparation, and performance under pressure.
Today, data science is the tool I use to analyze those same dynamics.

I’m particularly interested in:

  • Player performance & development metrics
  • Decision-making under uncertainty
  • Translating complex analysis into tools coaches and teams can understand

🌱 Currently Learning

  • Advanced geospatial analysis
  • Non-linear models for forecasting
  • Sports analytics workflows
  • Better data storytelling

📫 Let’s Connect

LinkedIn GitHub Email

🧰 Tech Stack & Tools

Python Pandas NumPy Scikit-learn PostgreSQL Tableau Git

Pinned Loading

  1. curso-geoespacial curso-geoespacial Public

    Forked from patymunoz/curso-geoespacial

    Copia de Paty!

    HTML 1

  2. 003_ML_Solution 003_ML_Solution Public

    Developing a Full implemented Machine Learning Pipeline about the analysis of a Trading Case defining interpretability from a Logistic Regression.

    Jupyter Notebook

  3. 004_LSTM 004_LSTM Public

    Development of a LSTM model for the NVDA stock behavior of the last 10 years of historical price data.

    Jupyter Notebook

  4. 005_RL-DQL_Trading 005_RL-DQL_Trading Public

    We explore the application of Reinforcement Learning (RL) / Deep Q-Learning (DQL)—to the domain of algorithmic trading and portfolio management.

    Jupyter Notebook 1

  5. 30-Days-Of-Python 30-Days-Of-Python Public

    Forked from Asabeneh/30-Days-Of-Python

    30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

    Python

  6. Baseball-Data-Analyst Baseball-Data-Analyst Public

    Im a data scientist in progress. Here you can see my real passion. Being venezuelan born, i've been taugh to have baseball in my veins. I've played my whole life (20 years old) and I am lucky to kn…