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dullibri/README.md

Hi 👋, ich bin Dirk

Data Engineer mit Data Science Hintergrund aus Deutschland

🔭 Woran ich aktuell arbeite

  • Wartung und Erweiterung eines Snowflake-Datawarehouses mit Medallion-Architektur
  • Hauptwerkzeuge: dbt, Airflow und Databricks
  • AWS-Umgebung mit CI/CD-Framework auf Bitbucket
  • Lerne Flutter für Mobile App Entwicklung
  • Rechtliche Einordnung von Zahlungsgarantien mit AWS Bedrock und Claude (Prompt Engineering)

🌱 Was ich gerade lerne

  • Flutter für Cross-Platform App-Entwicklung
  • Fortgeschrittenes Prompt Engineering mit Large Language Models

💼 Berufserfahrung

  • Data Engineer mit Fokus auf Cloud-Datenarchitekturen
  • Hintergrund in Data Science und maschinellem Lernen

🛠 Technologien & Tools

AWS Databricks Python Snowflake dbt Airflow Docker Git Flask MySQL TensorFlow scikit-learn Flutter

📫 Kontakt

LinkedIn Twitter

📊 GitHub Statistiken

Dirks GitHub Statistiken

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  1. pump_sensor pump_sensor Public

    Predicting really rare positives - a notebook on the pump_sensor data from kaggle. Including both simple indicator based approaches as well as machine learning.

    HTML 1 1

  2. titanic titanic Public

    The classical data science intro with Kaggle's titanic data set is used to illustrate a simple but entire data science life-cycle including model optimization, train-test-split, eda and cleaning.

    Jupyter Notebook 2

  3. Understanding_AfD_electoral_success Understanding_AfD_electoral_success Public

    A data set and an AI analysis of the electoral success of Germany's right wing party AfD including a Random Forest based machine learning approach.

    Jupyter Notebook 3 3

  4. DaxRendite DaxRendite Public

    App for illustration of yields of regular investment in German DAX

    R

  5. zeit-2 zeit-2 Public

    Analysis of web-scrapped news articles of DIE ZEIT. Construction of a sentiment indicator out of the articles and employment in a state-of-the-art economic prediction set-up demonstrating its usefu…

    R 1

  6. immo_bee immo_bee Public

    Scrape housing data from German housing portal Immowelt.de and retrieve as comma separted file.

    Jupyter Notebook 2