ch
Feedback

不要被骗子欺骗!Telemetrio 会找到并标记这些频道 👉 如果想查看标记,请订阅

Learn Python Coding

Learn Python Coding

前往频道在 Telegram

Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho

显示更多

📈 Telegram 频道 Learn Python Coding 的分析概览

频道 Learn Python Coding (@pythonre) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 890 名订阅者,在 技术与应用 类别中位列第 3 300,并在 印度 地区排名第 9 135 位。

📊 受众指标与增长动态

自 невідомо 创建以来,项目保持高速增长,吸引了 40 890 名订阅者。

根据 10 十一月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 114,过去 24 小时变化为 -12,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 2.20%。内容发布后 24 小时内通常能获得 0.90% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 898 次浏览,首日通常累积 370 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2。
  • 主题关注点: 内容集中在 math, harvard, oxford, supervision, waybienad 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
“Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho”

凭借高频更新(最新数据采集于 11 十一月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

Buy Ad
40 890
订阅者
-1224 小时
+107 天
+11430 天
帖子存档
PyTorch Pocket Reference: Building and Deploying Deep Learning Models (2021) Invite your friends 🌹🌹 @DataScience_Books

PyTorch Pocket Reference: Building and Deploying Deep Learning Models (2021) 👇👇👇👇👇
PyTorch Pocket Reference: Building and Deploying Deep Learning Models (2021) 👇👇👇👇👇

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines (2021) Invite your friends 🌹🌹 @DataScience_Books

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines (2021) 👇👇👇👇👇
Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines (2021) 👇👇👇👇👇

Title: Building the machine learning model. Invite your friends ❤️ @CodeProgrammer
Title: Building the machine learning model. Invite your friends ❤️ @CodeProgrammer

REACT 17 DESIGN PATTERNS AND BEST PRACTICESTHIRD EDITION (2021) Invite your friends 🌹🌹 @DataScience_Books

REACT 17 DESIGN PATTERNS AND BEST PRACTICESTHIRD EDITION (2021) 👇👇👇👇👇
REACT 17 DESIGN PATTERNS AND BEST PRACTICESTHIRD EDITION (2021) 👇👇👇👇👇

React Hooks in Action: With Suspense and Concurrent Mode MEAP V3 (2021) Invite your friends 🌹🌹 @DataScience_Books

React Hooks in Action: With Suspense and Concurrent Mode MEAP V3 (2021) 👇👇👇👇👇
React Hooks in Action: With Suspense and Concurrent Mode MEAP V3 (2021) 👇👇👇👇👇

WordPress 5 Cookbook: Actionable Solutions to Common Problems When Building Websites with WordPress (2020) Invite your friends 🌹🌹 @DataScience_Books

WordPress 5 Cookbook: Actionable Solutions to Common Problems When Building Websites with WordPress (2020) 👇👇👇👇👇
WordPress 5 Cookbook: Actionable Solutions to Common Problems When Building Websites with WordPress (2020) 👇👇👇👇👇

Programming Scala: Scalability = Functional Programming + Objects (2021) Invite your friends 🌹🌹 @DataScience_Books

Programming Scala: Scalability = Functional Programming + Objects (2021) 👇👇👇👇👇
Programming Scala: Scalability = Functional Programming + Objects (2021) 👇👇👇👇👇

Arduino Workshop, 2nd Edition: A Hands-on Introduction with 65 Projects (2021) PDF Format: https://t.me/DataScience2019/4090 Invite your friends 🌹🌹 @DataScience_Books

Arduino Workshop, 2nd Edition: A Hands-on Introduction with 65 Projects (2021) 👇👇👇👇👇
Arduino Workshop, 2nd Edition: A Hands-on Introduction with 65 Projects (2021) 👇👇👇👇👇

Artificial Intelligence A Textbook (2021) Invite your friends 🌹🌹 @DataScience_Books

Artificial Intelligence A Textbook (2021) 👇👇👇👇👇
Artificial Intelligence A Textbook (2021) 👇👇👇👇👇

The hundred-page machine learning book (2019) Invite your friends 🌹🌹 @DataScience_Books

The hundred-page machine learning book (2019) 👇👇👇👇👇
The hundred-page machine learning book (2019) 👇👇👇👇👇

👁 MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding MMOCR is an open-source toolbox based on
👁 MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition Github: https://github.com/open-mmlab/mmocr Paper: https://arxiv.org/abs/2108.06543v1 Documentation: https://mmocr.readthedocs.io/en/latest/ Invite your friends 🌹🌹 @DataScience_Books