sklearn-to-ts
Thomas Meissner v1.0.0
Train sklearn models (MLP, Random Forest, Linear Regression), export weights to JSON, and generate pure TypeScript inference code with zero npm dependencies. Handles the full pipeline: feature engi...
From the developer
License
MIT
Works with
Claude Code
Description
From the marketplace listing
Train sklearn models (MLP, Random Forest, Linear Regression), export weights to JSON, and generate pure TypeScript inference code with zero npm dependencies. Handles the full pipeline: feature engineering, synthetic data generation, model training, weight export, and TypeScript codegen. The resulting model runs server-side (Node.js/Next.js) or client-side (browser) in <1ms with a ~10-50 KB weights file. No Python runtime, no ONNX, no TensorFlow.js needed at runtime.
What changed
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Files & skills
sklearn-to-ts · catalog manifest
Saved declaration
{}
sklearn-to-ts · catalog manifest
Saved declaration
{
"name": "sklearn-to-ts",
"source": {
"sha": "d80d5cb7e693e9b1c949cb273103d7d315a1f0e5",
"url": "https://github.com/TGKMeissner/sklearn-to-typescript-inference.git",
"source": "url"
},
"homepage": "https://github.com/TGKMeissner/sklearn-to-typescript-inference",
"description": "Train sklearn models (MLP, Random Forest, Linear Regression), export weights to JSON, and generate pure TypeScript inference code with zero npm dependencies. Handles the full pipeline: feature engineering, synthetic data generation, model training, weight export, and TypeScript codegen. The resulting model runs server-side (Node.js/Next.js) or client-side (browser) in <1ms with a ~10-50 KB weights file. No Python runtime, no ONNX, no TensorFlow.js needed at runtime."
}
sklearn-to-ts · catalog manifest
Saved declaration
{
"name": "sklearn-to-ts",
"author": {
"url": "https://github.com/TGKMeissner",
"name": "Thomas Meissner"
},
"license": "MIT",
"version": "1.0.0",
"homepage": "https://github.com/TGKMeissner/sklearn-to-typescript-inference",
"repository": "https://github.com/TGKMeissner/sklearn-to-typescript-inference",
"description": "Train sklearn models (MLP, Random Forest, Linear Regression), export weights to JSON, and generate pure TypeScript inference code with zero npm dependencies. Handles the full pipeline: feature engineering, synthetic data generation, model training, weight export, and TypeScript codegen. Runs server-side or client-side in <1ms. Use cases include prediction models for fitness (race times, VO2max, recovery), SaaS (churn, lead scoring), e-commerce (pricing, delivery estimates), and more."
}
plugin.json observed Nov 6, 2026 · 10:49 UTC. Manifest source ↗
Catalog declarations and available plugin.json metadata are saved. Referenced skills and executable source files are not downloaded or tested. Missing components in a manifest do not prove that the plugin has none.
Installation instructions
Community
/plugin marketplace add anthropics/claude-plugins-community
/plugin install sklearn-to-ts@claude-communityTechnical details
- Sources
- Community
- First seen
- Oct 3, 2026 · 22:13 UTC
- Last seen
- Nov 7, 2026 · 18:00 UTC
- Latest observed change
- Oct 3, 2026 · 22:13 UTC
- Collection status
- Listed
- Reported installs
- Not provided
Installation counts are source-reported, not independently verified active users. Observation dates are not release dates.
Download plugin data (JSON)Plugin history: served from cache. Prepared . Refreshed when catalog data changes or after 6 hours. Your account and Follow status are live.