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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 41 818 subscribers, ranking 3 219 in the Technologies & Applications category and 15 236 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 41 818 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.

41 818
Subscribers
+424 hours
-627 days
-10230 days
Posts Archive
Deep Learning and the Game of Go @datascienceiot

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python @pythonlbooks

Практическая статистика для специалистов Data Science @datascienceiot

Data Analysis @datascienceiot

Classic Computer Science Problems in Swift Github @datascienceiot
Classic Computer Science Problems in Swift Github @datascienceiot

Mastering OpenCV 4 with Python - 2019 @pythonlbooks

Теоретический минимум по Big Data. Всё, что нужно знать о больших данных Github @datascienceiot
Теоретический минимум по Big Data. Всё, что нужно знать о больших данных Github @datascienceiot

Machine Learning in Finance (2020) Github @datascienceiot
Machine Learning in Finance (2020) Github @datascienceiot

Learn Data Analysis with Python: Lessons in Coding @pythonlbooks

The Elements of Statistical Learning Github @datascienceiot
The Elements of Statistical Learning Github @datascienceiot

Applied Statistics: Theory and Problem Solutions with R Github @datascienceiot
Applied Statistics: Theory and Problem Solutions with R Github @datascienceiot

Applied Machine Learning with Python Github @datascienceiot
Applied Machine Learning with Python Github @datascienceiot

Linear Algebra and Optimization for Machine Learning Github @datascienceiot
Linear Algebra and Optimization for Machine Learning Github @datascienceiot

SQL for Data Analytics (2019) Github @datascienceiot
SQL for Data Analytics (2019) Github @datascienceiot

Natural Language Processing with Python and spaCy: A Practical Introduction @datascienceiot

Discovering_Computer_Science_Interdisciplinary_Problems,_Principles.epub19.72 MB

A Programmer's Guide to Computer Science @datascienceiot

Machine Learning with R: Expert techniques for predictive modeling (2019) @datascienceiot

Discovering Computer Science : Interdisciplinary Problems, Principles, and Python Programming @datascienceiot

Задача для мобильных разработчиков и специалистов по анализу данных в рамках онлайн-хакатона SberCode. Разработай мобильное п
Задача для мобильных разработчиков и специалистов по анализу данных в рамках онлайн-хакатона SberCode. Разработай мобильное приложение для просмотра отзывов и их тональности или для просмотра падений приложения. Поборись за призовой фонд в 1 млн рублей! Участвовать в хакатоне можно из любой точки. Изучить эти и другие задачи можно на сайте sbercode.tech