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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
Algorithms @datascienceiot

Machine Learning with Spark™ and Python, Second Edition - 2020 @datascienceiot

Image operators image processing in Python Kinser, Jason M (2019) @datascienceiot

Python for Beginners : An Essential Guide to Easy Learning with Basic Exercises : Python programming Crash Course for Data Analysis and for Beginner Hackers Walsh, Conley (2020) @pythonlbooks

Learn Algorithmic Trading (2019) @datascienceiot

Machine Learning A Bayesian and Optimization Perspective Github @datascienceiot
Machine Learning A Bayesian and Optimization Perspective Github @datascienceiot

Neural Networks and Deep Learning: A Textbook (2019) Github @datascienceiot
Neural Networks and Deep Learning: A Textbook (2019) Github @datascienceiot

Praise for Deep Learning Illustrated book Github @datascienceiot
Praise for Deep Learning Illustrated book Github @datascienceiot

Data Science Fundamentals for Python and MongoDB Github @datascienceiot
Data Science Fundamentals for Python and MongoDB Github @datascienceiot

First Contact with Deep Learning Practical Introduction with Keras @datascienceiot

Data Science in Production (2020) Github @datascienceiot
Data Science in Production (2020) Github @datascienceiot

Mastering Object-Oriented Python (2019) @pythonl

Grokking Deep Learning (2019) Github @datascienceiot
Grokking Deep Learning (2019) Github @datascienceiot

Deep Learning System to Screen Coronavirus Disease @datascienceiot
Deep Learning System to Screen Coronavirus Disease @datascienceiot

Data Visualization: A Practical Introduction (2018) Github @datascienceiot
Data Visualization: A Practical Introduction (2018) Github @datascienceiot

Обратите внимание: @kaicode (5 сентября). Это первый в своём роде сбор на одной площадке авторов open source проектов, в Моск
Обратите внимание: @kaicode (5 сентября). Это первый в своём роде сбор на одной площадке авторов open source проектов, в Москве. Huawei спонсирует и организует. Отошлите им ссылку на свой GitHub проект, его рассмотрят и лучших пригласят на площадку для выступления и защиты. Три проекта получают в руки по $5000 каждый и возможность дальнейшей поддержки от Huawei. Пишите им в Телеграм группу за подробностями и бесплатным билетом на вход.

TensorFlow 2.0 Pocket Primer Github @datascienceiot
TensorFlow 2.0 Pocket Primer Github @datascienceiot

Artificial Intelligence For Dummies @datascienceiot

Essential Discrete Mathematics for Computer Science (2019) @datascienceiot

Python for Linguists @datascienceiot