Browsing: Data

There’s a growing assumption that if you connect a large language model (LLM) to your production system or application, it will simply “know” how to answer…

As LLM-powered agents move from research to production, one design tension is becoming harder to ignore: the more useful cloud-hosted memory becomes, the more private user…

learning data science in 2020, Pandas was one of the most popular tools. Although new tools focus on improving Pandas’ weaknesses in handling very large datasets,…

. A part of me started this journey because data engineering is one of the hottest and highest-paying careers right now. I’m not going to pretend…

model fails not because the algorithm is weak, but because the variables were not prepared in a way the model can properly understand? In credit risk…

Joe Rose, president at strategic technology provider JBS Dev, wants to cut through one of the myths of working with generative and agentic AI systems. “It’s…

any time in the data engineering world, you’ve likely encountered this debate at least once. Maybe twice. Ok, probably a dozen times😉 “Should we process our…

(not that long ago) when being a data scientist meant living in a notebook, tweaking hyperparameters as if your life depended on it, and in a…

— I wasn’t actively looking for Polars. I’ve been on a bit of a Pandas optimization journey lately. First, I wrote about why you should stop…

, as in life, it’s important to know what you’re working with. Python’s dynamic type system appears to make this difficult at first glance. A type…