REPOGEO REPORT · LITE

alexsosn/iOS_ML

Default branch master · commit 655cfdcc · scanned 6/25/2026, 8:58:32 PM

GitHub: 1,428 stars · 150 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

28 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 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 alexsosn/iOS_ML, 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

Clarify README's opening to emphasize it's a curated list of resources, not examples or libraries

Why:

CURRENT

# Machine Learning for iOS 

**Last Update: January 12, 2018.**

Curated list of resources for iOS developers in following topics:

COPY-PASTE FIX

# Awesome Machine Learning for iOS: A Curated List of Resources 

**Last Update: January 12, 2018.**

This repository provides a comprehensive, curated list of resources for iOS developers interested in Machine Learning, AI, and Natural Language Processing. Unlike direct libraries or examples, this is a meta-resource designed to help you discover suitable tools, libraries, and learning materials for integrating ML into your iOS applications.

highlicense#2

Add a LICENSE file to the repository

Why:

CURRENT

(no LICENSE file detected — the repo has no recognizable license)

COPY-PASTE FIX

Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).

mediumtopics#3

Add more specific topics to reinforce the 'curated list' nature of the repo

Why:

CURRENT

artificial-intelligence, awesome-list, computer-vision, deep-learning, gpgpu, machine-learning, natural-language-processing, neural-network, speech-recognition, swift

COPY-PASTE FIX

Add the following topics: ios-ml-resources, ml-libraries-list, ios-development-resources, curated-list, awesome-ios-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 alexsosn/iOS_ML

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Core ML

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Core ML · recommended 2×
TensorFlow Lite · recommended 2×
PyTorch Mobile · recommended 2×
Create ML · recommended 2×
Vision · recommended 1×

CATEGORY QUERY
What are the best libraries for integrating machine learning and AI into iOS applications?
you: not recommended
AI recommended (in order):
1. Core ML
2. Vision
3. Natural Language (NL)
4. TensorFlow Lite
5. PyTorch Mobile
6. ML Kit (Firebase)
7. Create ML
AI recommended 7 alternatives but never named alexsosn/iOS_ML. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How can I add computer vision or natural language processing features to my Swift application?
you: not recommended
AI recommended (in order):
1. Core ML
2. Vision Framework
3. Natural Language Framework
4. Create ML
5. TensorFlow Lite
6. PyTorch Mobile
AI recommended 6 alternatives but never named alexsosn/iOS_ML. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
Suggestion:
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 alexsosn/iOS_ML?
pass
AI named alexsosn/iOS_ML explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts alexsosn/iOS_ML in production, what risks or prerequisites should they evaluate first?
pass
AI named alexsosn/iOS_ML 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 alexsosn/iOS_ML solve, and who is the primary audience?
pass
AI did not name alexsosn/iOS_ML — 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?

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/alexsosn/iOS_ML.svg)](https://repogeo.com/en/r/alexsosn/iOS_ML)

HTML

<a href="https://repogeo.com/en/r/alexsosn/iOS_ML"><img src="https://repogeo.com/badge/alexsosn/iOS_ML.svg" alt="RepoGEO" /></a>

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alexsosn/iOS_ML — 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