There are 3 machine learning topics I am actively thinking about a lot these days:

Topic #1: Evaluation

I am interested in evaluation because it is at the core of every functioning real-world machine learning system.

Kaggle introduced me to it—and since then, I have learned a lot about the importance of baseline models, i.i.d., and cross-validation.

Topic #2: Reproducibility

I first got interested in reproducibility 13 years ago.

And my hope is that over the next year as an SSI fellow, as I continue to learn and share more, I'll be able to help move reproducibility in machine learning applications in science along.

Topic #3: Operations

I also have an interest in learning more about ML ops.

It's one of those fun rabbit holes I find growing deeper and deeper with every topic I read up on.

It would be great to connect with other people who are interested in these same topics — so if any of the above resonates, feel free to reach out!

3 Machine Learning Topics I Am Exploring Right Now Atomic Essay by Jesper Dramsch