REPOGEO REPORT · LITE

vaaaaanquish/Awesome-Rust-MachineLearning

Default branch main · commit 45d42d89 · scanned 5/9/2026, 5:17:24 AM

GitHub: 2,252 stars · 125 forks

AI VISIBILITY SCORE

27 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface vaaaaanquish/Awesome-Rust-MachineLearning, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition the README's opening to explicitly state it's an 'Awesome List'

Why:

CURRENT

This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers. This repository is targeted at people who are thinking of migrating from Python. 🦀🐍

COPY-PASTE FIX

This is an **Awesome List** of machine learning libraries and resources written in Rust. It's a comprehensive compilation of GitHub repositories, blogs, books, movies, discussions, and papers, specifically targeted at developers migrating from Python to Rust for machine learning. 🦀🐍

mediumtopics#2

Correct typo in topics and add 'awesome-list'

Why:

CURRENT

awasome, deep-learning, image-processing, machine-learning, machine-learning-library, natural-language-processing, rust, rust-library

COPY-PASTE FIX

awesome, awesome-list, deep-learning, image-processing, machine-learning, natural-language-processing, rust

lowabout#3

Enhance the 'About' description to include 'Awesome List'

Why:

CURRENT

This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀

COPY-PASTE FIX

An Awesome List of machine learning libraries and resources for Rust, compiling GitHub repos, blogs, books, and papers. Ideal for Python developers migrating to Rust for ML. 🦀

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface vaaaaanquish/Awesome-Rust-MachineLearning

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

tch-rs

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

tch-rs · recommended 1×
burn · recommended 1×
ndarray · recommended 1×
linfa · recommended 1×
rust-bert · recommended 1×

CATEGORY QUERY
What are the best machine learning libraries available for Rust development?
you: not recommended
AI recommended (in order):
1. tch-rs
2. burn
3. ndarray
4. linfa
5. rust-bert
6. candle
AI recommended 6 alternatives but never named vaaaaanquish/Awesome-Rust-MachineLearning. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking Rust alternatives to common Python machine learning frameworks for data science.
you: not recommended
AI recommended (in order):
1. Linfa
2. Tch-rs
3. Rust-GSL
4. SmartCore
5. Candle
6. Polars
AI recommended 6 alternatives but never named vaaaaanquish/Awesome-Rust-MachineLearning. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of vaaaaanquish/Awesome-Rust-MachineLearning?
pass
AI did not name vaaaaanquish/Awesome-Rust-MachineLearning — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts vaaaaanquish/Awesome-Rust-MachineLearning in production, what risks or prerequisites should they evaluate first?
pass
AI named vaaaaanquish/Awesome-Rust-MachineLearning explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo vaaaaanquish/Awesome-Rust-MachineLearning solve, and who is the primary audience?
pass
AI did not name vaaaaanquish/Awesome-Rust-MachineLearning — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of vaaaaanquish/Awesome-Rust-MachineLearning. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/vaaaaanquish/Awesome-Rust-MachineLearning.svg)](https://repogeo.com/en/r/vaaaaanquish/Awesome-Rust-MachineLearning)

HTML

<a href="https://repogeo.com/en/r/vaaaaanquish/Awesome-Rust-MachineLearning"><img src="https://repogeo.com/badge/vaaaaanquish/Awesome-Rust-MachineLearning.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

vaaaaanquish/Awesome-Rust-MachineLearning — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite