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DS По всем вопросам- @haarrp @ai_machinelearning_big_data - machine learning @pythonl - Python @itchannels_telegram - 🔥 best it channels @ArtificialIntelligencedl - AI @pythonlbooks-📚 @programming_books_it -📚 Реестр РКН: https://clck.ru/3Fk3zS

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📈 Analytical overview of Telegram channel Data Science

Channel Data Science (@datascienceiot) is an active participant. Currently, the community unites 41 817 subscribers, ranking 3 211 in the Technologies & Applications category and 15 203 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 41 817 subscribers.

According to the latest data from 27 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -102 over the last 30 days and by 4 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 5.68%. Within the first 24 hours after publication, content typically collects 2.42% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 374 views. Within the first day, a publication typically gains 1 011 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
  • Thematic interests: Content is focused on key topics such as llm, агентов, api, октября, разработчиков.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
DS По всем вопросам- @haarrp @ai_machinelearning_big_data - machine learning @pythonl - Python @itchannels_telegram - 🔥 best it channels @ArtificialIntelligencedl - AI @pythonlbooks-📚 @programming_books_it -📚 Реестр РКН: https://clck.ru/3...

Thanks to the high frequency of updates (latest data received on 28 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

41 817
Subscribers
+424 hours
-627 days
-10230 days
Posts Archive
Git Essentials @datascienceiot

@yegor256news is an author's English-speaking channel by Yegor Bugayenko, a programmer, blogger, author of Elegant Objects, c
@yegor256news is an author's English-speaking channel by Yegor Bugayenko, a programmer, blogger, author of Elegant Objects, creator of Zerocracy platform and a regular speaker at many major IT-conferences; subscribe and follow his publications!

Algorithms for Dummies @datascienceiot

Practical Automated Machine Learning on Azure: Using Azure Machine Learning to Quickly Build AI Solutions @datascienceiot

Clever Algorithms @datascienceiot

Internet of Things and Data Analytics Handbook @datascienceiot

Mining Social Media: Finding Stories in Internet Data (2019) @datascienceiot
Mining Social Media: Finding Stories in Internet Data (2019) @datascienceiot

Comprehensive guide on Machine Learning @datascienceiot
Comprehensive guide on Machine Learning @datascienceiot

Gray Hat C#: A Hacker's Guide to Creating and Automating Security Tools @datascienceiot
Gray Hat C#: A Hacker's Guide to Creating and Automating Security Tools @datascienceiot

Guide to Natural Language Processing Github @datascienceiot
Guide to Natural Language Processing Github @datascienceiot

Python Programming for Biology: Bioinformatics and Beyond @pythonl

KB – Neural Data Mining with Python @datascienceiot
KB – Neural Data Mining with Python @datascienceiot

Machine Learning Yearning An Amazing Book By Andrew Ng @datascienceiot
Machine Learning Yearning An Amazing Book By Andrew Ng @datascienceiot

Mastering Natural Language Processing with Python Github @datascienceiot
Mastering Natural Language Processing with Python Github @datascienceiot

Python Deep Learning, Second Edition - 2019 Github @datascienceiot
Python Deep Learning, Second Edition - 2019 Github @datascienceiot

Python Web Scraping @pythonl

Learning Internet of Things @datascienceiot

Python for Data Analysis, 2nd edition - 2019 @datascienceiot

Generative Adversarial Networks with python @datascienceiot

Practical Data Science with Python 3: Synthesizing Actionable Insights from - 2019 @datascienceiot