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datascienceinfo

前往频道在 Telegram

🧠The learning hub for Data Science, ML and AI 1) Data Science 2) Machine Learning 3) Data viz 4) Artificial Intelligence 5) Quizzes 6) Ebooks 7) Articles

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📈 Telegram 频道 datascienceinfo 的分析概览

频道 datascienceinfo (@data_science_info) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 32 337 名订阅者,在 教育 类别中位列第 5 908,并在 印度 地区排名第 12 757

📊 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 32 337 名订阅者。

根据 23 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 -428,过去 24 小时变化为 -14,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 2.92%。内容发布后 24 小时内通常能获得 1.52% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 944 次浏览,首日通常累积 493 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2
  • 主题关注点: 内容集中在 aws, enthusiast, bedrock, developer, engineer 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:
🧠The learning hub for Data Science, ML and AI 1) Data Science 2) Machine Learning 3) Data viz 4) Artificial Intelligence 5) Quizzes 6) Ebooks 7) Articles

凭借高频更新(最新数据采集于 24 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。

32 337
订阅者
-1424 小时
-957
-42830
帖子存档
#FREE MASTERCLASS 🚀 Gen AI & Agentic AI Specialization Course Learn to build real AI Agents, Multi-Agent Systems, and RAG pi
#FREE MASTERCLASS 🚀 Gen AI & Agentic AI Specialization Course Learn to build real AI Agents, Multi-Agent Systems, and RAG pipelines using MCP & A2A — across AWS, Azure, and GCP. 💻 100% Hands-on | 3 Months | 25+ Projects | Personal Mentorship*l 🎯 Perfect for: _Software Engineers, Data Scientists, Cloud/DevOps Engineers & Developers ready to move into high-paying GenAI & Agentic AI roles._ ⚡ Only Seats Available Filling Fast! 👇🏻 https://aiagent.psitrontech.com 💬 Please share this with your friends & network — help someone level up their AI career! 🙏

Al will replace your job - but only if you're actually smart enough to be replaced.: Look at this chart. The gap between what
Al will replace your job - but only if you're actually smart enough to be replaced.: Look at this chart. The gap between what Al can do vs what people actually use it for is massive. White-collar workers in legal, management, and business are sleeping on this. Meanwhile, the 'Al will take all jobs' crowd conveniently ignores that food service and construction barely register. The truth? Most people aren't losing their jobs to Al. They're losing them to people who use Al - and this data proves most of you still aren't one of them.

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Transformers are powerful. But they have hard limits. Key takeaways from the NYU expert panel: • LLMs fail beyond short plann
Transformers are powerful. But they have hard limits. Key takeaways from the NYU expert panel: • LLMs fail beyond short planning horizons • No true continual learning • No live weight updates • Memory is simulated, not persistent • Language alone is not general intelligence The next AI architecture will focus on reasoning and real memory systems. Full video link below https://www.youtube.com/live/o9o7fU_ZSIE?si=lNzzq8EYiFjItoli

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I’ve started sharing practical AI tools & workflows on my YouTube channel — no hype, only what actually works. If you want AI explained simply (not technical), you’ll like my YouTube channel 👇 https://youtube.com/@prasadwithai?si=9fZneiffXK45r_iO