现已上线！2025 年 Telegram 研究 — 年度关键洞察 
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 39 366 名订阅者，在 技术与应用 类别中位列第 3 444，并在 印度 地区排名第 10 033 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 39 366 名订阅者。
根据 25 六月, 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 442，过去 24 小时变化为 19，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 1.40%。内容发布后 24 小时内通常能获得 0.97% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 552 次浏览，首日通常累积 381 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 26 六月, 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。
39 366
订阅者
+1924 小时
+727 天
+44230 天
帖子存档
39 368
📚 Numerical Methods Using Java (2022)
🔗 Download Link: https://wikile.org/Qgc4
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✅ By: @DataScience_Books 🌟
39 368
📚 Data Analysis & Dashboarding with Microsoft Excel (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Interactive tools for machine learning, Deep learning and math
🔗 GitHub Link: https://wikile.org/oj2s10
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✅ By: @DataScience_Books 🌟
39 368
📚 Optimization for Data Analysis (2022)
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✅ By: @DataScience_Books 🌟
39 368
Repost from Data Science Books
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39 368
📚 Applied Missing Data Analysis (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 R in Action (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Julia for Data Analysis (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Data Analysis and Related Applications (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Pattern Recognition and Data Analysis with Applications (2022)
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✅ By: @DataScience_Books 🌟
39 368
Full Stack Deep Learning course edition is Marvelous, in case you haven’t checked out. Great content and presentation, and the course is FREE for everyone. All the lectures are available on YouTube.
✅ Lecture 1: Course Vision and When to Use ML
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✅ Lecture 5 : Deployment
✅ Lecture 6: Continual Learning
✅ Lecture 7: Foundation Models
✅ Lecture 8: ML Teams and Project Management
✅ Lecture 9: Ethics
Check out the full videos and detailed notes on their website
🔗 Enroll Link: https://wikile.org/rU9kcA
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✅ By: @DataScience_Books 🌟
39 368
📚 Modern Classification and Data Analysis (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Practical Nest.js (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Deep Learning for EEG-based Brain-computer Interfaces (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Object Detection with Deep Learning Models (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Evolutionary Deep Learning (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Deep learning with TensorFlow and Keras (2022)
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✅ By: @DataScience_Books 🌟
39 368
📚 Accelerate Deep Learning Workloads with Amazon SageMaker (2022)
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✅ By: @DataScience_Books 🌟
