umap-learn SKILL.md skillA
umap-learn from marielynneblock/arcanum-artifex is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add marielynneblock/arcanum-artifex/umap-learn@git:20260710.0115f49Pins git:20260710.0115f49 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- marielynneblock/arcanum-artifex
- Path
skills/data-science/umap-learn/SKILL.md- Versions recorded
- 5
- Latest version
- git:20260710.0115f49, committed Jul 10, 2026
- First version recorded
- Apr 6, 2026
- Size
- 15,400 bytes
- Repository stars
- 4
- License
- none declared
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualisation, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# UMAP-Learn ## Overview UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique for visualisation and general non-linear dimensionality reduction. Apply this skill for fast, scalable embeddings that preserve local and global structure, supervised learning, and clustering preprocessing. ## Quick Start ### Installation ```bash uv pip install umap-learn ``` ### Basic Usage UMAP follows scikit-learn conventions and can be used as a drop-in replacement for t-SNE or PCA. ```python import umap from sklearn.preprocessing import StandardScaler # Prepare data (standardization is essential) scaled_data = StandardScaler().fit_transform(data) # Method 1: Single step (fit and transform) embedding = umap.UMAP().fit_transform(scaled_data) # Method 2: Separate steps (for reusing trained model) reducer = umap.UMAP(random_state=42) reducer.fit(scaled_data) embedding = reducer.embedding_ # Access the trained embedding ``` **Critical preprocessing requirement:** Always standardise features to comparable scales before applying UMAP to ensure equal weighting across dimensions. ### Typical Workflow ```python import umap import matplotlib.pyplot as plt …
Read the whole file at its exact version.
How to install
mdr add marielynneblock/arcanum-artifex/umap-learn@sha256:1ad830a3b3580787The line at the top of this page pins the label git:20260710.0115f49, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_lqktl63thjuu333w)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Apr 6, 2026 and Jul 10, 2026, about one every 24 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260710.0115f49 latest | 2026-07-10 | 0115f49 | 15,400 B | A | view · diff |
| git:20260710.d1b3aa8 | 2026-07-10 | d1b3aa8 | 15,393 B | A | view · diff |
| git:20260710.ffb3400 | 2026-07-10 | ffb3400 | 15,393 B | A | view · diff |
| git:20260515.b861afb | 2026-05-15 | b861afb | 15,393 B | A | view · diff |
| git:20260406.05dff34 | 2026-04-06 | 05dff34 | 15,394 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (15400 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
marielynneblock/arcanum-artifex · 4 stars · license none declared · pushed 2026-09-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_lqktl63thjuu333w GET https://markdownregistry.com/api/v1/resolve?ref=marielynneblock/arcanum-artifex/umap-learn GET https://markdownregistry.com/api/v1/blob/1ad830a3b3580787a354fe3448477d79eabd1e5a2175d4ee771dc6a5abe959de
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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