Dasha Herrmannova

Data Scientist @ElsevierConnect. Interested in #HealthcareAI, #NLProc, #ML. Previously @ornl & @oacore. One day I'll visit Mars

[Dasha Herrmannova @robodasha]

💡Final thought: Improving reproducibility isn’t just about following best practices—it’s about building trust in the results we share and ensuring that our work stands the test of time.

[Dasha Herrmannova @robodasha]

Improving Reproducibility of Gen AI Evaluations

Would you trust results that you can’t reproduce? Reproducibility is the backbone of trust in AI research. Without it, we risk misleading conclusions, wasted effort, and barriers to meaningful innovation.

[Dasha Herrmannova @robodasha]

There are a lot more insights in the paper that won't fit in this post. If you care about reproducibility, I can highly recommend giving it a read.

[Dasha Herrmannova @robodasha]

I think this is one of the most important skills to master as a data scientist. Do you agree?

[Dasha Herrmannova @robodasha]

In my last post, I shared why I believe learning NLP is a smart investment—even as generative AI takes center stage.

Today, I wanted to share my three favorite resources to learn NLP.

[Dasha Herrmannova @robodasha]

Is Learning NLP Still Worth It In The Age Of Generative AI?

Here's why I think learning foundational NLP skills is a great investment.

[Dasha Herrmannova @robodasha]

If you're interested in building evaluations for generative AI applications, I highly recommend this blog post by Hamel Husain: Creating a LLM-as-a-Judge That Drives Business Results https://t.co/MCnvSClhgX
Here are a few reasons why:

[Dasha Herrmannova @robodasha]

One of my goals for 2025 is to write more. Today feels like a good day to start :)