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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 77 693 名订阅者,在 教育 类别中位列第 2 010,并在 印度 地区排名第 3 829 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 77 693 名订阅者。

根据 09 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 -87,过去 24 小时变化为 -6,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 3.23%。内容发布后 24 小时内通常能获得 0.99% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 512 次浏览,首日通常累积 770 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 4。
  • 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 10 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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77 693
订阅者
-624 小时
-377 天
-8730 天
帖子存档
Explainable Deep Learning AI.pdf18.32 MB

+3
Machine Learning Techniques for Text.pdf30.33 MB

Probabilistic Machine Learning for Finance and Investing.pdf21.17 MB

Join us for an exhilarating Python Singula Meetup Online! 🌐🎉 We bring together Python enthusiasts, developers, and learners
Join us for an exhilarating Python Singula Meetup Online! 🌐🎉  We bring together Python enthusiasts, developers, and learners from around the world! 🗓️ Date: August 29 ⏰Time: 6:00pm CET 🔗 To sign up 📺 The meetup will be broadcasted via YouTube!  Our lineup of esteemed speakers will dive into exciting topics: ▶Discover the reasons behind Python's occasional slowness in specific tasks ▶Learn practical strategies to secure a Hadoop cluster within a large ML team ▶Unleash the power of spatial data with expert feature engineering 📌Subscribe to our Telegram channel, where you can find all the latest announcements for upcoming meetups!

Neural Networks from Scratch in Python.pdf42.65 MB

Chat GPT for Data Science Interview 👇👇 https://t.me/datasciencefree/250

Deep Learning Book.pdf5.28 MB

Learn AI-Assisted Python Programming.pdf6.03 MB

Encyclopedia of Data Science and Machine Learning John Wang, 2023

Machine Learning from Weak Supervision.pdf37.05 MB

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MERCENARIES MEDIA - a lie gets halfway around the world before the truth has a chance to get its pants on. Read the truth!
MERCENARIES MEDIA - a lie gets halfway around the world before the truth has a chance to get its pants on. Read the truth!

"Master in-demand skills @₹99/year Don't miss out on this once-in-a-lifetime opportunity. 🔥 Get access to 150+ Top Certifica
"Master in-demand skills @₹99/year Don't miss out on this once-in-a-lifetime opportunity. 🔥 Get access to 150+ Top Certification Courses and Job @ ₹99/year 🤑 Apply here: https://bit.ly/3OGOVE8 💯 Python 💯 Django 💯 Web Development 💯 Artificial Intelligence 💯 Machine Learning 💯 AWS 💯 Interview Preparation & more premium courses ...and many more Offer ending soon⌛"

Morris_H_DeGroot_Mark_J_Schervish_Probability_and_statistics_Pearson.pdf6.13 MB

Mathematical Foundation of Computer Science Y.N. Singh, 2005

📚 9 must-have Python developer tools. 1. PyCharm IDE 2. Jupyter notebook 3. Keras 4. Pip Package 5. Python Anywhere 6. Sciki
📚 9 must-have Python developer tools. 1. PyCharm IDE 2. Jupyter notebook 3. Keras 4. Pip Package 5. Python Anywhere 6. Scikit-Learn 7. Sphinx 8. Selenium 9. Sublime Text

"📊 Data Analysis Tip: Have you ever wondered how outliers can impact your analysis? Outliers are data points that significantly differ from the rest of your dataset. They can skew results and affect the accuracy of your insights. Tip: Before removing outliers, it's essential to understand their origin. Are they errors, natural variations, or something else? Removing or adjusting them without proper justification can lead to biased results.

Machine Learning with Python.pdf28.13 MB

Probability Distributions Cheat Sheet.pdf2.57 MB