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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 75 933 名订阅者,在 教育 类别中位列第 2 103,并在 印度 地区排名第 4 204

📊 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 75 933 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 731,过去 24 小时变化为 33,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 2.95%。内容发布后 24 小时内通常能获得 0.86% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 239 次浏览,首日通常累积 650 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 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。

75 933
订阅者
+3324 小时
+587
+73130
帖子存档
Udacity(udacity.com) courses collections Udacity's Android Basics Nanodegree Download Link- https://mega.nz/folder/nDgXkaob#5LPk0Hpz4HgZ7njcvyNmqw @datasciencefun Udacity's Machine Learning Engineer Nanodegree Download Link- https://mega.nz/folder/qX5BWKDD#s6JadsuGzsyELin6zYfU8Q @datasciencefun Udacity's Blockchain Nanodegree Download Link- https://mega.nz/folder/HD43EKTL#jcAo2OvAjEQmi0SqHELuyA Udacity's Data Analyst Nanodegree Download Link- https://mega.nz/folder/GbgnkCaR#gQodlI6pEkoKGIaqDhuCUg

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Which of the following is an important library or framework for data visualization using PYTHON? [Not Machine learning]
Anonymous voting

Data science Tools
Data science Tools

Building the Machine Learning Model
Building the Machine Learning Model

Which step is done just after collecting data?
Anonymous voting

Do you want more books recommendations?
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Hello guys, if you are a beginner in data science and want to learn it from scratch. Then, there is a good news for you. Currently Amazon is providing 77% off on this data science book Highly recommend if you are beginner in data science Purchase it before the price increases https://bit.ly/30j72GI Flipkart is selling the same book for rs. 2500 https://bit.ly/39K2pIJ Enjoy learning 👍

👩🏻‍💻 Why should one study Linear Algebra for ML? 👉🏼 Clearly, to develop a better intuition for machine learning and deep learning algorithms and not treat them as black boxes. This would allow you to choose proper hyper-parameters and develop a better model. You would also be able to code algorithms from scratch and make your own variations to them as well. 👉🏼 Learn Linear Algebra for Machine Learning with: Khan Academy: https://www.khanacademy.org/math/linear-algebra Udacity: https://www.udacity.com/course/linear-algebra-refresher-course--ud953 Coursera: https://www.coursera.org/learn/linear-algebra-machine-learning Here are some amazing freely available ebooks on the same topic: Mathematics for Machine Learning: https://mml-book.github.io/book/mml-book.pdf An Introduction to Statistical Learning: https://faculty.marshall.usc.edu/gareth-james/ISL/ Happy machine learning! 🎉

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