RRepoGEO

REPOGEO REPORT · LITE

explosion/spacy-course

Default branch master · commit 77d8ee16 · scanned 6/20/2026, 4:23:13 PM

GitHub: 2,422 stars · 376 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)

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

AI VISIBILITY SCORE
33 /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
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 explosion/spacy-course, 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
    Emphasize the official, free, self-paced nature in the README intro

    Why:

    CURRENT
    This repo contains both an **online course**, as well as its modern open-source web framework. In the course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
    COPY-PASTE FIX
    This repository provides the **official, free, and self-paced online course** for Advanced NLP with spaCy, directly from its creators. You'll learn to build advanced natural language understanding systems using both rule-based and machine learning approaches, all within a modern open-source web framework.
  • mediumreadme#2
    Add a 'Why this course?' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps after the introduction, titled "Why this spaCy Course?" or "What makes this course unique?". Content could include: "This course stands out as the official training resource from Explosion AI, the creators of spaCy. It's entirely free, self-paced, and focuses on practical, production-ready NLP with spaCy, distinguishing it from general academic courses or broad machine learning libraries."
  • lowreadme#3
    Clarify the role of the web framework component in the README

    Why:

    CURRENT
    This repo contains both an **online course**, as well as its modern open-source web framework.
    COPY-PASTE FIX
    This repository primarily hosts an **online course** for Advanced NLP with spaCy. It also includes the modern open-source web framework that powers the course's interactive learning experience.

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 explosion/spacy-course
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 2×
  2. fast.ai's Practical Deep Learning for Coders · recommended 2×
  3. Stanford CS224N · recommended 1×
  4. Hugging Face's NLP Course · recommended 1×
  5. huggingface/datasets · recommended 1×
  • CATEGORY QUERY
    Where can I find a free online course to learn advanced natural language processing?
    you: not recommended
    AI recommended (in order):
    1. Stanford CS224N
    2. Hugging Face's NLP Course
    3. Transformers library (huggingface/transformers)
    4. Datasets library (huggingface/datasets)
    5. Tokenizers library (huggingface/tokenizers)
    6. fast.ai's Practical Deep Learning for Coders
    7. fastai library (fastai/fastai)
    8. DeepLearning.AI's Natural Language Processing Specialization
    9. Coursera
    10. Google's Machine Learning Crash Course

    AI recommended 10 alternatives but never named explosion/spacy-course. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good resources for self-study in machine learning for text analysis?
    you: not recommended
    AI recommended (in order):
    1. Coursera: DeepLearning.AI's Natural Language Processing Specialization
    2. Speech and Language Processing by Jurafsky and Martin
    3. Hugging Face Transformers Library (huggingface/transformers)
    4. fast.ai's Practical Deep Learning for Coders
    5. Applied Text Analysis with Python by Benjamin Bengfort, Tony Ojeda, and Rebecca Bilbro
    6. Kaggle Learn
    7. spaCy (explosion/spaCy)

    AI recommended 7 alternatives but never named explosion/spacy-course. 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 explosion/spacy-course?
    pass
    AI did not name explosion/spacy-course — 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 explosion/spacy-course in production, what risks or prerequisites should they evaluate first?
    pass
    AI named explosion/spacy-course 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 explosion/spacy-course solve, and who is the primary audience?
    pass
    AI named explosion/spacy-course explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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explosion/spacy-course — 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