Juan Torchia's Technical Blog

Tag: python

Sep 16 2026

XGBoost Doesn't Beat scikit-learn, It Solves a Different Problem

With a small, reproducible dataset in Jupyter, I compare what XGBoost actually does differently from scikit-learn's RandomForest — and why the answer isn't "which one is better" but "which problem is this for."

Sep 16 2026 · 8′ · Tutorials · machine learning · python

8′

Sep 05 2026

That messy 4000-line notebook taught me to stop hating Jupyter

Why Jupyter is still the de facto standard for exploring data, even though versioning it with git will make you want to smash your keyboard.

Sep 05 2026 · 5′ · Experiments · python · data science

5′

Jun 29 2026

XGBoost: the gradient boosting that dominated Kaggle and survived the hype

XGBoost isn't a trend — it's the algorithm that won hundreds of ML competitions on tabular data. Why it's still the mandatory reference in 2025 and when you should reach for it.

Jun 29 2026 · 5′ · Experiments · machine learning · open source

5′

Jun 26 2026

PyTorch: the deep learning framework that won the war

PyTorch showed up in 6 independent awesome lists and the reason is simple: it won. This isn't hype — it's infrastructure. Here's why it made our list and when it actually makes sense to use it.

Jun 26 2026 · 5′ · Experiments · machine learning · deep learning

5′

Jun 23 2026

TensorFlow: the ML elephant that's still standing

TensorFlow isn't sexy in 2025, but it's still the serious infrastructure behind deployment at scale. Why it made the list and when you actually need it.

Jun 23 2026 · 5′ · Experiments · machine learning · deep learning

5′

May 08 2026

Supply chain npm vs PyPI: I compared both simulations and the most dangerous vector isn't what everyone thinks

I ran supply chain attack simulations on npm and PyPI separately. When I put them side by side, the pattern that emerged made me uncomfortable: the ecosystem everyone watches isn't the most vulnerable one. Here's the cross-meta-analysis with real numbers.

May 08 2026 · 9′ · Experiments · npm · node.js

9′

May 01 2026

Malware in PyTorch Lightning: I Simulated the Same Supply Chain Attack Vector on My ML Dependencies in Production

The Python ML ecosystem has a structural problem that Node and Rust solved years ago: the transitive dependency chain of a single ML library can exceed 200 entries, most without verifiable cryptographic signatures. I simulated the same vector against my own stack — and what I found is not reassuring

May 01 2026 · 8′ · Experiments · devops · produccion

8′

Apr 18 2026

I Wrote a Python Interpreter in Python. What I Learned Has Nothing to Do With Python

A 150-point HN post sent me down a rabbit hole building a Python interpreter from scratch. I didn't learn Python. I learned exactly where AI lies to me when it generates code.

Apr 18 2026 · 6′ · Experiments · LLM · arquitectura

6′

Apr 16 2026

The Local LLM Ecosystem Doesn't Need Ollama (And That Made Me Uncomfortable)

I've been team Ollama since day one. Last week I tried replacing it with raw llama.cpp and a minimal wrapper. What I found forced me to rethink something I thought I'd already figured out: Ollama solves UX, not infrastructure.

Apr 16 2026 · 6′ · Opinion · docker · LLM

6′