Data Science
Posts about Data Science
Numpyro: Probabilistic Programming That Doesn’t Waste My Time
I remember the bad old days of probabilistic programming. You’d define a hierarchical model, hit “sample,” and then—I’m not joking—go watch an entire.
Taipy: Why I Finally Ditched Streamlit for Production Apps
Well, I have a confession to make. For the last five years, I’ve been utterly hooked on “script-to-web” tools.
PyScript in 2026: Why I Finally Stopped Hating Client-Side Python
Actually, I should clarify – I remember sitting in the audience at PyCon 2022 when PyScript was first announced.
Stop Rewriting Your Pandas Code for Spark. Seriously.
I looked at my terminal yesterday and saw the one error message that has haunted my entire career in data engineering.
NASA Just Paid to Fix NumPy’s Messy Parts. About Time.
I was staring at a flame graph at 11 p.m. last Tuesday, wondering why my seemingly simple data pipeline was eating RAM like Chrome with fifty tabs open.
Stop Downsampling Your Data: The New Pandas Update is Actually Good
I have a confession to make. For the last five years, I’ve been lying to my stakeholders. Not big lies—just little white lies about data granularity.
Mojo in 2025: A Python Dev’s Honest Look Under the Hood
I have a love-hate relationship with Python. We all do, right? It’s the glue holding the entire AI ecosystem together, yet every time I watch a profiler.
Keras in Late 2025: Why Transfer Learning Is Finally Boring
I spent yesterday afternoon trying to squeeze a Vision Transformer (ViT) onto a consumer-grade GPU. A few years ago, this would have been a three-coffee.
Stop Wrestling with HTML: Why I Switched to Flet
I am tired of pretending that I enjoy writing HTML and CSS. For years, every time I needed to build a user interface for a Python script or a data tool, I.
Strengthening the Core: The Future of NumPy, Scikit-learn, and Scientific Python Performance
The Python ecosystem has long been the dominant force in data science, machine learning, and scientific computing.