REPOGEO REPORT · LITE
yandexdataschool/Practical_RL
Default branch master · commit 6f7fa8bc · scanned 6/26/2026, 9:12:08 AM
GitHub: 6,527 stars · 1,804 forks
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.
3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
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.
- highreadme#1Reposition the README H1 to explicitly state it's a practical course
Why:
CURRENT# Practical_RL
COPY-PASTE FIX# Practical_RL: An Open Course on Practical Reinforcement Learning
- highhomepage#2Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIXAdd the official course website URL (e.g., 'https://your-course-website.com' or 'https://github.com/yandexdataschool/Practical_RL' if the repo is the primary landing page).
- mediumtopics#3Add 'jupyter-notebooks' to the repository topics
Why:
CURRENTcourse-materials, deep-learning, deep-reinforcement-learning, git-course, hacktoberfest, keras, mooc, pytorch, pytorch-tutorials, reinforcement-learning, tensorflow
COPY-PASTE FIXcourse-materials, deep-learning, deep-reinforcement-learning, git-course, hacktoberfest, jupyter-notebooks, keras, mooc, pytorch, pytorch-tutorials, reinforcement-learning, tensorflow
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.
- Deep Reinforcement Learning (UC Berkeley, CS285) by Sergey Levine · recommended 1×
- Spinning Up in Deep RL by OpenAI · recommended 1×
- Deep Reinforcement Learning by David Silver (UCL) · recommended 1×
- Reinforcement Learning: An Introduction (Richard S. Sutton and Andrew G. Barto) · recommended 1×
- Practical Deep Reinforcement Learning by The School of AI (Siraj Raval) · recommended 1×
- CATEGORY QUERYWhere can I find an open course on practical deep reinforcement learning?you: not recommendedAI recommended (in order):
- Deep Reinforcement Learning (UC Berkeley, CS285) by Sergey Levine
- Spinning Up in Deep RL by OpenAI
- Deep Reinforcement Learning by David Silver (UCL)
- Reinforcement Learning: An Introduction (Richard S. Sutton and Andrew G. Barto)
- Practical Deep Reinforcement Learning by The School of AI (Siraj Raval)
- Deep Reinforcement Learning Nanodegree by Udacity (with Georgia Tech)
AI recommended 6 alternatives but never named yandexdataschool/Practical_RL. This is the gap to close.
Show full AI answer
- CATEGORY QUERYRecommend a reinforcement learning course offering practical labs and assignments.you: not recommendedAI recommended (in order):
- Coursera
- NumPy
- Udacity
- OpenAI Gym
- fast.ai
- PyTorch
- Google Cloud
- TensorFlow
- Keras
- edX
- OpenAI Spinning Up in Deep RL
AI recommended 11 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 completenesswarn
Suggestion:
- README presencepass
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?passAI named yandexdataschool/Practical_RL explicitly
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?passAI 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?passAI 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?
Embed your GEO score
Drop this badge into the README of yandexdataschool/Practical_RL. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
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yandexdataschool/Practical_RL — 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