Acutize
Clean, analyze, forecast, and model data—without code
What it does
Acutize is a no-code data workspace that turns CSV, Excel, JSON, and Parquet files into clean datasets, business insights, forecasts, ML model comparisons, and export-ready reports. Built for analysts, operators, and teams. Start free.
Clean CSV, Excel, JSON, and Parquet datasets, analyze data quality, generate business insights, compare ML models, forecast metrics, and export reports without writing scripts.
Turn CSV, Excel, JSON, and Parquet files into clean datasets, business insights, forecasts, model recommendations, and export-ready reports in one guided browser workspace. Clean missing support ticket values and review category encoding before model preview. Acutize brings data preparation, exploration, model recommendations, preview comparison, and exports into one practical workspace for business datasets. Upload CSV, Excel, JSON, or Parquet files and inspect rows, columns, data types, missing values, duplicates, and quality signals before taking action. Clean common dataset problems with guided options for missing values, duplicates, categorical encoding, scaling, and repeatable…from acutize.com
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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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