Dyakonov/DL

• highreadme#1

  Explicitly state the repository's purpose and content in the README's opening

  原因：

  当前

  # «Глубокое обучение» (Deep Learning)
  * образовательный проект по глубокому обучению

  复制粘贴的修复

  复制

  # Репозиторий курса «Глубокое обучение» (Deep Learning)
  Этот репозиторий содержит полный набор материалов для курса по глубокому обучению, включая лекции, слайды и видеозаписи.

  待办完成忽略
• highlicense#2

  Add a LICENSE file and declare the license in the README

  原因：

  复制粘贴的修复

  复制

  1. Create a LICENSE file in the repository root with the text of the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
  2. Add the following section to your README:
  ## Лицензия
  Материалы этого курса распространяются под лицензией Creative Commons Attribution 4.0 International (CC BY 4.0).

  待办完成忽略
• mediumhomepage#3

  Add a homepage URL and refine the 'About' description

  原因：

  复制粘贴的修复

  复制

  Set the repository homepage to: `https://www.youtube.com/playlist?list=PLaRUeIuewv8BYOrm6HBgJKbGUD-jcBQpW`
  Update the repository description to: `Полный набор материалов для курса "Глубокое обучение (Deep Learning)" от ВМК МГУ, включая лекции, слайды и видеозаписи.`

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  Where can I find comprehensive online courses or lecture series to learn deep learning fundamentals?

  你：未被推荐
  AI 推荐顺序：

  1. Deep Learning Specialization by Andrew Ng
  2. fast.ai's "Practical Deep Learning for Coders"
  3. PyTorch
  4. Deep Learning with PyTorch: A 60 Minute Blitz
  5. MIT 6.S191
  6. Neural Networks and Deep Learning by Michael Nielsen
  7. Google's Machine Learning Crash Course
  8. TensorFlow
  9. Deep Learning A-Z™: Hands-On Artificial Neural Networks
  10. Keras

  AI 推荐了 10 个替代方案，却始终没点名 Dyakonov/DL。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Seeking structured university-level materials for a deep learning curriculum, including slides and video lectures.

  你：未被推荐
  AI 推荐顺序：

  1. Stanford CS231n
  2. Stanford CS224n
  3. DeepLearning.AI
  4. University of Oxford - Deep Learning
  5. MIT 6.S191
  6. fast.ai Practical Deep Learning for Coders
  7. University of Toronto - CSC321

  AI 推荐了 7 个替代方案，却始终没点名 Dyakonov/DL。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of Dyakonov/DL?

  pass
  ⚠AI 未点名 Dyakonov/DL —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts Dyakonov/DL in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 Dyakonov/DL

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo Dyakonov/DL solve, and who is the primary audience?

  pass
  ⚠AI 未点名 Dyakonov/DL —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？