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Data Science

Data Science

前往频道在 Telegram

DS По всем вопросам- @haarrp @ai_machinelearning_big_data - machine learning @pythonl - Python @itchannels_telegram - 🔥 best it channels @ArtificialIntelligencedl - AI @pythonlbooks-📚 @programming_books_it -📚 Реестр РКН: https://clck.ru/3Fk3zS

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Machinelearning网络:Machinelearning俄罗斯15 220技术与应用3 224

📈 Telegram 频道 Data Science 的分析概览

频道 Data Science (@datascienceiot) 是活跃参与者。目前社区聚集了 41 788 名订阅者，在 技术与应用 类别中位列第 3 224，并在 俄罗斯 地区排名第 15 220 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 41 788 名订阅者。

根据 29 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 -138，过去 24 小时变化为 -23，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 6.03%。内容发布后 24 小时内通常能获得 2.45% 的反应，占订阅者总量。
  • 帖子覆盖： 每篇帖子平均可获得 2 520 次浏览，首日通常累积 1 024 次浏览。
  • 互动与反馈： 受众积极参与，单帖平均反应数为 0。
  • 主题关注点： 内容集中在 llm, агентов, api, октября, разработчиков 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：
“DS По всем вопросам- @haarrp @ai_machinelearning_big_data - machine learning @pythonl - Python @itchannels_telegram - 🔥 best it channels @ArtificialIntelligencedl - AI @pythonlbooks-📚 @programming_books_it -📚 Реестр РКН: https://clck.ru/3...”

凭借高频更新（最新数据采集于 30 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。

41 788
订阅者
-2324 小时
-747 天
-13830 天
帖子存档
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👍Top posts of last week: Can Blockchain Provide a Secure Platform for M2M Transactions? https://t.me/Internet_of_things_channel/607 How to Survive and Thrive in Our Hyperconnected World https://t.me/Internet_of_things_channel/600 IoT in Education: The Smartboard https://t.me/Internet_of_things_channel/597 Your Guide to a Successful Cloud Migration https://t.me/Internet_of_things_channel/591

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Building IoT (Internet of Things) Solutions Approach and Methodology for building IoT solutions. https://www.udemy.com/building-iot-internet-of-things-solutions/

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I'll make more content now (3-5 post everyday).

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Navigation for channel👍 #IoT #AI #ML #AR #Future #Hacking #WiFi #Security #Blockchain #book_of_the_day

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#book_of_the_day Database Design, 2nd Edition This book covers database systems and database design concepts. It provides short, easy-to-read explanations of how to get database design right the first time. It also offers numerous examples to help you avoid the many pitfalls that entrap new and not-so-new database designers. Database design is not an exact science. Many are surprised to find that problems with their databases are caused by poor design rather than by difficulties in using the database management software. This book helps you ask and answer important questions about your data so you can understand the problem you are trying to solve and create a pragmatic design capturing the essentials while leaving the door open for refinements and extension at a later stage.

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