RRepoGEO

REPOGEO REPORT · LITE

llSourcell/Learn-Natural-Language-Processing-Curriculum

Default branch master · commit c02ae581 · scanned 6/18/2026, 9:38:07 PM

GitHub: 1,052 stars · 296 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
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 llSourcell/Learn-Natural-Language-Processing-Curriculum, 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
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["nlp", "natural-language-processing", "curriculum", "course", "learning-path", "python", "pytorch", "nltk", "machine-learning", "deep-learning"]
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the repository root to clarify usage rights.
  • mediumreadme#3
    Emphasize the 'video-centric, curated curriculum' nature in the README's opening

    Why:

    CURRENT
    # Learn-Natural-Language-Processing-Curriculum
This is the curriculum for "Learn Natural Language Processing" by Siraj Raval on Youtube
    COPY-PASTE FIX
    # Learn-Natural-Language-Processing-Curriculum
This repository provides a comprehensive, video-centric, and curated curriculum for "Learn Natural Language Processing" by Siraj Raval on Youtube.

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 llSourcell/Learn-Natural-Language-Processing-Curriculum
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. fast.ai's Practical Deep Learning for Coders, Part 2: NLP (2023 Edition) · recommended 1×
  3. Coursera's DeepLearning.AI NLP Specialization · recommended 1×
  4. TensorFlow · recommended 1×
  5. Hugging Face's NLP Course · recommended 1×
  • CATEGORY QUERY
    Looking for a comprehensive curriculum to learn natural language processing from scratch.
    you: not recommended
    AI recommended (in order):
    1. fast.ai's Practical Deep Learning for Coders, Part 2: NLP (2023 Edition)
    2. PyTorch
    3. Coursera's DeepLearning.AI NLP Specialization
    4. TensorFlow
    5. Hugging Face's NLP Course
    6. Hugging Face ecosystem
    7. Stanford CS224N: Natural Language Processing with Deep Learning
    8. NPTEL's Introduction to Natural Language Processing

    AI recommended 8 alternatives but never named llSourcell/Learn-Natural-Language-Processing-Curriculum. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources offer a practical NLP course using Python, PyTorch, and NLTK?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. NLTK

    AI recommended 2 alternatives but never named llSourcell/Learn-Natural-Language-Processing-Curriculum. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 llSourcell/Learn-Natural-Language-Processing-Curriculum?
    pass
    AI did not name llSourcell/Learn-Natural-Language-Processing-Curriculum — 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 llSourcell/Learn-Natural-Language-Processing-Curriculum in production, what risks or prerequisites should they evaluate first?
    pass
    AI named llSourcell/Learn-Natural-Language-Processing-Curriculum 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 llSourcell/Learn-Natural-Language-Processing-Curriculum solve, and who is the primary audience?
    pass
    AI did not name llSourcell/Learn-Natural-Language-Processing-Curriculum — 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

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llSourcell/Learn-Natural-Language-Processing-Curriculum — 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