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Buceando un nuevo y atractivo mundo
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Buceando un nuevo y atractivo mundo

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GMEpelbaum/README.md

👋 I'm a sociologist, political advisor, and teacher with a passion for uncovering the hidden stories within data. My journey has taken me from traditional research methods to the exciting world of data science, where I'm using informatic tools like to analyze complex social phenomena.

👀 Director of the Arquetipos Ingeniería Política Consulting Firm

💪 Starting to dive into the world of data science

🌱Many years researching and asking questions to social reality with analog methods, now with new tools.

❤️ Passionate about data and the relationships between them.

📫I'm not the best, but I'm passionate about learning.

⚡️ Skills

  • Programming Languages: R, SQL, Stata, SPSS (some experience).
  • Machine Learning: Development & evaluation of various predictive models (logistic regression, random forest, XGBoost). Proficient in ensemble methods, including model stacking.
  • Data Wrangling & Preprocessing: Data cleaning, transformation, and feature engineering using R.
  • Data Visualization: Creating clear and informative visualizations using ggplot2 and other packages.
  • Database Management: Experience for data retrieval and manipulation.
  • Tools: RStudio.
  • Ongoing Learning: Expanding skills in Python and Power BI.

I'm deeply passionate about politics in all its forms, particularly the dynamic interplay between the public and private sectors.

Research and Articles:

Radio Interviews:

Other Works:

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Popular repositories Loading

  1. GMEpelbaum GMEpelbaum Public

    Config files for my GitHub profile.

  2. Arquetipeando Arquetipeando Public

    Here are some of the freely available works produced by my consulting firm, Arquetipos.

  3. studata studata Public

    While pursuing my Master's degree in Political Science at Universidad Torcuato Di Tella, I developed several projects focusing on data analysis. I am pleased to share these works with you.

  4. Predicting-and-stacking-with-Titanic-DF Predicting-and-stacking-with-Titanic-DF Public

    Predicting survival on the Titanic (common dataset) using: logistic model-random forest-stacking-XGBoost

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