• Machine Learning: I'm passionate about working with tabular data and ensemble methods (who doesn't like a random forest ). I have learned, I am still learning and I will always keep learning about robust and interpretable models that solve real-world problems.

• Statistical Methods: I always have an eye on the stats behind any method I train. Having experience in statistical modeling I always try to look for the underlying assumptions and limitations of various ML algorithms.

The data science space is just huge, and I am excited about improving my knowledge in all of the following fields.

• MLOps 🔄

• Deep Learning 🧠

• Recommendation Systems 🎯 [Expect updates soon ...]

• Computer Vision 📷

I am happy to keep growing my GitHub! These are the main repositories github.com/angelgldh has at the moment:

• ethz_school_work: A collection of projects from my university courses, covering topics like introductory ML methods, Bayesian approaches, and reinforcement learning.
• HackerRank: I regularly participate in HackerRank challenges. Most of the problems are part of the AI > Statistics and Machine Learning category.
• RSV modelling and transfer learning: Big research project I am working on right now!

Thanks for reading all of this!