Passionate about data engineering, API development, automation, and machine learning.
I love turning raw data into clean, valuable insights — and building robust pipelines that scale.
- 🧹 Data Cleaning & Prep (Pandas, Python, SQL)
- 🔍 Analysis & Visualization (Seaborn, Matplotlib, Power BI)
- 🤖 Machine Learning (Scikit-Learn, clustering, predictive modeling)
- ⚙️ API Development & Deployment (FastAPI, Flask, Render/Railway)
- 🏗️ ETL & Pipelines (Airflow basics, automation scripts)
- 🌐 Web Scraping (BeautifulSoup, Requests – no Selenium)
Full-stack real estate data project. Scrapes property listings, builds a clean dataset, and integrates with the ImmoEliza-ML repo for predictive modeling.
Tech: Python, Web Scraping, Data Engineering, Machine Learning
Unsupervised ML clustering analysis on Chipotle order patterns.
Tech: Python, Pandas, Scikit-Learn, Jupyter
A fully deployed API with documentation + scalable structure.
Tech: FastAPI, Python, Deployment CI/CD
Languages:
Python, SQL, JavaScript (basics)
Libraries:
Pandas, NumPy, Scikit-Learn, FastAPI, Matplotlib, Seaborn
Tools:
GitHub, Docker, Visual Studio Code, Power BI, Jupyter
Cloud / DevOps:
Render, Railway, GitHub Actions (CI/CD)
- Improving API deployment workflow
- Structuring a full data portfolio
- Building more automated scrapers
- Getting better at cloud deployment (AWS / GCP basics)
📧 hornaertcharly@gmail.com
💼 LinkedIn: https://www.linkedin.com/in/charly-hornaert-2a568497/
🌍 GitHub: CharlyHo
🚀 Always building — always learning.