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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 41 818 名订阅者,在 技术与应用 类别中位列第 3 219,并在 俄罗斯 地区排名第 15 236

📊 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 41 818 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。

41 818
订阅者
+424 小时
-627
-10230
帖子存档
Build a Career in Data Science (2020) @datascienceiot

Neural Networks: A Visual Introduction for Beginners by Michael Taylor @datascienceiot

Practical time series analysis: master time series data processing, visualization, and modeling using Python @pythonlbooks

Machine Learning for Algorithmic Trading (2020) @datascienceiot

Linear Algebra and Learning from Data (2019) @datascienceiot

Natural Language Processing Recipes - 2019 Github @datascienceiot
Natural Language Processing Recipes - 2019 Github @datascienceiot

Mastering pandas for Finance Github @datascienceiot
Mastering pandas for Finance Github @datascienceiot

Artificial Intelligence for Big Data Github @datascienceiot
Artificial Intelligence for Big Data Github @datascienceiot

PySpark Recipes Github @datascienceiot
PySpark Recipes Github @datascienceiot

Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python - 2020 Github @datascienceiot
Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python - 2020 Github @datascienceiot

Practical Synthetic Data Generation (2020) Github @datascienceiot
Practical Synthetic Data Generation (2020) Github @datascienceiot

Deep Learning for Coders with fastai and PyTorch (2020) Github @datascienceiot
Deep Learning for Coders with fastai and PyTorch (2020) Github @datascienceiot

Intro to Python for Computer Science and Data Science - 2020 @pythonlbooks

Глубокое обучение без математики. Практика @datascienceiot
Глубокое обучение без математики. Практика @datascienceiot

Advanced Deep Learning with TensorFlow 2 and Keras (2020) @datascienceiot

Practical Natural Language Processing (2020) @datascienceiot

Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data @datascienceiot

Hands-On Data Analysis with Pandas - 2019 @datascienceiot

R Programming: A Step-by-Step Guide for Absolute Beginners (2020) @datascienceiot

Data Science and Analytics with Python @pythonlbooks