RRepoGEO

REPOGEO REPORT · LITE

yandexdataschool/Practical_RL

Default branch master · commit 6f7fa8bc · scanned 5/15/2026, 4:26:38 PM

GitHub: 6,498 stars · 1,802 forks

AI VISIBILITY SCORE
22 /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
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 yandexdataschool/Practical_RL, 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 core value proposition to emphasize practical labs

    Why:

    CURRENT
    An open course on reinforcement learning in the wild.
    COPY-PASTE FIX
    An open, hands-on course on reinforcement learning in the wild, featuring practical labs and assignments.
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/yandexdataschool/Practical_RL
  • mediumtopics#3
    Refine repository topics to emphasize 'practical' and 'labs'

    Why:

    CURRENT
    course-materials, deep-learning, deep-reinforcement-learning, git-course, hacktoberfest, keras, mooc, pytorch, pytorch-tutorials, reinforcement-learning, tensorflow
    COPY-PASTE FIX
    reinforcement-learning, deep-reinforcement-learning, course-materials, mooc, practical-labs, hands-on-learning, pytorch, tensorflow, keras, deep-learning, machine-learning-course

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 yandexdataschool/Practical_RL
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Reinforcement Learning (CS234) by Stanford University
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Reinforcement Learning (CS234) by Stanford University · recommended 1×
  2. Deep Reinforcement Learning by UC Berkeley · recommended 1×
  3. Reinforcement Learning: An Introduction · recommended 1×
  4. Reinforcement Learning by University College London · recommended 1×
  5. Practical Reinforcement Learning by National Research University Higher School of Economics · recommended 1×
  • CATEGORY QUERY
    Where can I find an open, practical course to learn modern reinforcement learning techniques?
    you: not recommended
    AI recommended (in order):
    1. Reinforcement Learning (CS234) by Stanford University
    2. Deep Reinforcement Learning by UC Berkeley
    3. Reinforcement Learning: An Introduction
    4. Reinforcement Learning by University College London
    5. Practical Reinforcement Learning by National Research University Higher School of Economics
    6. spinningup by OpenAI

    AI recommended 6 alternatives but never named yandexdataschool/Practical_RL. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for comprehensive course materials to master deep reinforcement learning with practical labs.
    you: not recommended
    AI recommended (in order):
    1. Deep Reinforcement Learning Nanodegree (Udacity)
    2. PyTorch
    3. TensorFlow
    4. Deep Reinforcement Learning (UC Berkeley - CS285)
    5. Python
    6. Practical Deep Reinforcement Learning (Coursera - University of Alberta)
    7. Keras
    8. Deep Reinforcement Learning (DeepLearning.AI - Coursera)
    9. Reinforcement Learning: An Introduction (Sutton & Barto)
    10. Deep Reinforcement Learning Hands-On (Packt Publishing book with code)

    AI recommended 10 alternatives but never named yandexdataschool/Practical_RL. 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 yandexdataschool/Practical_RL?
    pass
    AI did not name yandexdataschool/Practical_RL — 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 yandexdataschool/Practical_RL in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yandexdataschool/Practical_RL 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 yandexdataschool/Practical_RL solve, and who is the primary audience?
    pass
    AI did not name yandexdataschool/Practical_RL — 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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