Production-Grade Data PipelinesDistinguishing between production-grade data pipelines and amateur setups is crucial for organizations aiming to leverage their data…Feb 6Feb 6
How to Evaluate LLMsEvaluating LLMs is hard. LLMs are aimed at how well they predict the next word during training, and that’s what they are in fact good at…Jan 1Jan 1
Explaining vs. Predicting in practicePractical lessons for datascientists from the 2010 Galit Shmueli paper “To Explain or to Predict”.Sep 12, 2021Sep 12, 2021
Data Readiness LevelsIf you struggle with explaining why your data science project is difficult, it’s often down to data not being “ready to go”. But how to…May 3, 2021May 3, 2021
Learnings from AMLD — 3 Takeaways for Natural Language ProcessingNatural Language Processing has been booming since 2018 with BERT &c. In recent months, the field made even more progress. What gives?Mar 1, 2020Mar 1, 2020
Learnings from AMLD — Getting ML into production by Mikio BraunMikio Braun is staff scientist at GetYourGuide and was previously working as senior datascientist for Zalando. He might have an idea or…Feb 1, 2020Feb 1, 2020
Learnings from AMLD KeynotesToday, the fourth edition of Applied Machine Learning Days kicked off the main conference with a set of keynotes from corporate and…Jan 27, 2020Jan 27, 2020
