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Machine Learning & Artificial Intelligence | Data Science Free Courses

Machine Learning & Artificial Intelligence | Data Science Free Courses

前往频道在 Telegram

Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence Admin: @coderfun

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📈 Telegram 频道 Machine Learning & Artificial Intelligence | Data Science Free Courses 的分析概览

频道 Machine Learning & Artificial Intelligence | Data Science Free Courses (@datasciencefree) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 66 765 名订阅者,在 教育 类别中位列第 2 446,并在 马来西亚 地区排名第 431

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 66 765 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 519,过去 24 小时变化为 31,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 0.76%。内容发布后 24 小时内通常能获得 0.78% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 510 次浏览,首日通常累积 524 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 3
  • 主题关注点: 内容集中在 sellerflash, waybienad, pricing, buybox, buyer 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:
Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence Admin: @coderfun

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 教育 类别中的关键影响点。

66 765
订阅者
+3124 小时
+797
+51930
帖子存档
Machine Learning For Absolute Beginners.pdf2.64 MB

Data Science and Machine Learning.pdf20.05 MB

Zero to Deep Learning Francesco Mosconi, 2019

Distributed Machine Learning with PySpark (2023).pdf3.41 MB

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Exploring University Mathematics with Python.pdf23.61 MB

🚨 Last call – crypto bull market is about to begin. Bitcoin is preparing for the 2024 rally, leaving less time to enter at f
🚨 Last call – crypto bull market is about to begin. Bitcoin is preparing for the 2024 rally, leaving less time to enter at favorable prices. If you don't want to miss it, follow experienced traders like SZ from Hong Kong. Using his own trading strategy, he identifies the most profitable coins and shares them with his followers. Join now and see for yourself - https://t.me/+YQ6Yz3gLlaMwNjEy

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Free Data sets for Data Science & Machine Learning Projects 👇👇 https://t.me/DataPortfolio

Mastering OpenCV with Python Ayush Vaishya, 2023

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Learning OpenCV 5 Computer Vision with Python Joseph Howse, 2022