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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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📈 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 41 817 名订阅者,在 技术与应用 类别中位列第 3 211,并在 俄罗斯 地区排名第 15 203

📊 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 41 817 名订阅者。

根据 27 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 -102,过去 24 小时变化为 4,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 5.68%。内容发布后 24 小时内通常能获得 2.42% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 374 次浏览,首日通常累积 1 011 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 28 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。

41 817
订阅者
+424 小时
-627
-10230
帖子存档
Programming in Scala Fourth Edition: Updated for Scala 2.13 Github @datascienceiot
Programming in Scala Fourth Edition: Updated for Scala 2.13 Github @datascienceiot

The Book of R: A First Course in Programming and Statistics Github @datascienceiot
The Book of R: A First Course in Programming and Statistics Github @datascienceiot

Machine Learning. Step-by-Step Guide To Implement. Machine Learning Algorithms with Python Github @datascienceiot
Machine Learning. Step-by-Step Guide To Implement. Machine Learning Algorithms with Python Github @datascienceiot

Mathematics for Machine Learning (2020) @datascienceiot

Django for Professionals: Production websites with Python & Django (2019) @datascienceiot

Python Artificial Intelligence Projects for Beginners @pythonlbooks

Practical Quantum Computing for Developers: Programming Quantum Rigs in the Cloud using Python, Quantum Assembly Language and IBM QExperience @datascienceiot

Hands-On Deep Learning for Images with TensorFlow @datascienceiot

Python ® Machine Learning - 2019 @pythonlbooks

Marketing Analytics. Optimize Your Business with Data Science in R, Python, and SQL @pythonlbooks

The Hundred-Page Machine Learning Book (2019) @datascienceiot

Reinforcement Learning : With Open AI, TensorFlow and Keras Using Python @datascienceiot

Graph Algorithms: Practical Examples in Apache Spark and Neo4j @datascienceiot

Foundations for Analytics with Python

Building Machine Learning Powered Applications (2020) Github @datascienceiot
Building Machine Learning Powered Applications (2020) Github @datascienceiot

Python Data Visualization Cookbook @pythonlbooks

Practical Deep Learning for Cloud, Mobile, and Edge (2019) Github @datascienceiot
Practical Deep Learning for Cloud, Mobile, and Edge (2019) Github @datascienceiot

Artificial Vision and Language Processing for Robotics Github @datascienceiot
Artificial Vision and Language Processing for Robotics Github @datascienceiot

Programming Quantum Computers: Essential Algorithms and Code Samples Github @datascienceiot
Programming Quantum Computers: Essential Algorithms and Code Samples Github @datascienceiot

Bayesian Statistics The Fun Way (2019) Github @datascienceiot
Bayesian Statistics The Fun Way (2019) Github @datascienceiot