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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 75 833 名订阅者,在 教育 类别中位列第 2 106,并在 印度 地区排名第 4 234

📊 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 75 833 名订阅者。

根据 21 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 770,过去 24 小时变化为 8,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 3.15%。内容发布后 24 小时内通常能获得 1.09% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 385 次浏览,首日通常累积 827 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 22 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。

75 833
订阅者
+824 小时
+717
+77030
帖子存档
Data Science Roadmap from GeekforGeeks
Data Science Roadmap from GeekforGeeks

Do you want roadmap for becoming data scientist in this channel?
Anonymous voting

+1
Real-World Machine Learning Henrik Brink, 2017

All keyboard shortcuts for data scientist (1).pdf3.15 MB

Neural Networks from Scratch in Python Harrison Kinsley, 2020

Pandas Ebook.pdf1.76 MB

+3
The Quick Python Book Naomi Ceder, 2018

Beginning programming with python for dummies John Paul Mueller, 2014

Let’s stay ahead of the market together and make money. The Analyst offers excellent ways to discover new trading opportuniti
Let’s stay ahead of the market together and make money. The Analyst offers excellent ways to discover new trading opportunities, NFT, Metaverse, and gem calls without doing the analysis and searching yourself. Join now for free.

+3
Data_Science_for_Business_With_R_Jeffrey_S_Saltz,_Jeffrey_Morgan.epub25.31 MB

Advanced Data Analytics Using Python With Machine Learning, Deep Learning and NLP Examples #book #Ml

Every ML project should keep the following documentation: • Change log • Tech debt log • Potential risks • Experiment logs •
Every ML project should keep the following documentation: • Change log • Tech debt log • Potential risks • Experiment logs • Future work ideas • List of assumptions • ETL pipeline description

Python_Seaborn_Cheat_Sheet.pdf6.24 KB

Repost from Coding Projects
Natural Language Processing Projects Akshay Kulkarni, 2022

Mastering Numerical Computing With NumPy.pdf6.19 MB

Continuous Machine Learning with Kubeflow Aniruddha Choudhury, 2022

Efficient Methods for DL.pdf9.72 MB

➡️ Become a Data Scientist with "Learnbay's Data Science Certification Course" in just 6 Months. Apply Now and get 100% Place
➡️ Become a Data Scientist with "Learnbay's Data Science Certification Course" in just 6 Months. Apply Now and get 100% Placement Assistance along with 150% Salary Hike🚀 📌 Apply here for free Counselling session : Click Here

+1
Big_Data_Surveillance_And_Security_Intelligence_The_Canadian_Case.pdf2.69 MB