Netron lets you inspect the architecture of any ML model — no Jupyter, no code, no drama. ONNX, PyTorch, TensorFlow: open it and see everything.
Jul 05 2026 · 5′ · Experiments · tooling · machine learning
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
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
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
lode reimplements DVC's hot path in Go with a non-negotiable invariant: byte-identical compatibility with DVC 3.x. Static binary, parallel hashing, state DB that avoids re-hashing. No migration, no lock-in. But pipelines are out of scope and benchmarks have context. Here's why that perimeter is an honest technical decision, not a limitation to hide.
Jun 21 2026 · 7′ · Experiments · machine learning · open source
I followed the viral 241-point HN tutorial and documented every dollar spent, every GPU hour, and every disappointment. My thesis: training an LLM from scratch in 2025 is a valid technical exercise, but calling it "an alternative to Claude" is lying to yourself.
May 05 2026 · 9′ · Experiments · LLM · ia
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
Train in Python, deploy in Java, Go, or whatever you've got. m2cgen converts your scikit-learn models into native code with zero runtime dependencies.
Apr 18 2026 · 5′ · Experiments · machine learning · open source
I saw the title and figured it was clickbait. I sat down, read the paper, and had to get up and walk around. MegaTrain proposes training 100B+ parameter models on a single GPU in full precision. I won't use it tomorrow. But it shifts who can do what — and that matters to me.
Apr 09 2026 · 9′ · Technology · machine learning · LLMs
Architecture, real systems, product decisions and technical lessons. Everything reviewed with my own judgment before it ships.
213 articles published