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不要被骗子欺骗!Telemetrio 会找到并标记这些频道 👉 如果想查看标记,请订阅

Data Science & Machine Learning

Data Science & Machine Learning

前往频道在 Telegram

Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

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📈 Telegram 频道 Data Science & Machine Learning 的分析概览

频道 Data Science & Machine Learning (@datasciencefun) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 77 647 名订阅者,在 教育 类别中位列第 2 015,并在 印度 地区排名第 3 825 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 77 647 名订阅者。

根据 12 十一月, 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 -123,过去 24 小时变化为 -21,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 2.52%。内容发布后 24 小时内通常能获得 1.01% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 1 954 次浏览,首日通常累积 781 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 learning, accuracy, distribution, panda, dataset 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:
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data”

凭借高频更新(最新数据采集于 13 十一月, 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。

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77 647
订阅者
-2124 小时
-767 天
-12330 天
帖子存档
thebook_ Introduction to Machine Learning.pdf10.31 MB

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Pattern Recognition and Machine Learning.pdf4.52 MB

Pattern Recognition and Machine Learning [ Information Science and Statistics ] Christopher M. Bishop #python #machinelearning #statistics #information #ai #ml

Follow the latest IT, computer science and entrepreneurship news on Hacker News Digest Telegram channel Hacker News (news.ycombinator.com) – is one of the most influential social news websites. It was here that Drew Houston first introduced Dropbox to the world.   Hacker News Digest Telegram channel will send you the top 10 most popular posts from Hacker News, daily. Subscribe to stay up-to-date!

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Machine Learning Cheatsheet #python #ml #cheatsheet #ai

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Machine Learning Notes - TutorialsDuniya.pdf14.65 MB

You are given a data set. The data set has missing values which spread along 1 standard deviation from the median. What percentage of data would remain unaffected? Why? Answer: This question has enough hints for you to start thinking! Since, the data is spread across median, let’s assume it’s a normal distribution. We know, in a normal distribution, ~68% of the data lies in 1 standard deviation from mean (or mode, median), which leaves ~32% of the data unaffected. Therefore, ~32% of the data would remain unaffected by missing values.

🔰 Python for Machine Learning & Data Science Masterclass ⏱ 44 Hours 📦 170 Lessons Learn about Data Science and Machine Lear
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