Data Science
Posts about Data Science
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.
Mastering Modern Keras: Multi-Backend Workflows and Ecosystem Integration
Introduction: The Evolution of Deep Learning Frameworks The landscape of deep learning has undergone a seismic shift in recent years.
Unlocking Bacterial Metabolism: Deep Learning and Knowledge Graphs with the IBIS Framework
The landscape of bacterial genomics is undergoing a seismic shift. As sequencing technologies become cheaper and more accessible, the volume of genomic.
Mastering Python Finance: From Data Gathering to Advanced Algorithmic Trading Strategies
The financial technology landscape has undergone a seismic shift over the last decade, transitioning from spreadsheet-dominated workflows to.
Marimo Notebooks: The Reactive Revolution in Python Data Science
For over a decade, the Jupyter notebook has been the de facto standard for data exploration, scientific computing, and machine learning education.