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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
Deep Learning for Natural Language Processing: Creating Neural Networks with Python Github @datascienceiot
Deep Learning for Natural Language Processing: Creating Neural Networks with Python Github @datascienceiot

Introducing Data Science @datascienceiot
Introducing Data Science @datascienceiot

Beginning Artificial Intelligence with the Raspberry Pi Github @datascienceiot
Beginning Artificial Intelligence with the Raspberry Pi Github @datascienceiot

Deep Reinforcement Learning with Guar Performance @datascienceiot
Deep Reinforcement Learning with Guar Performance @datascienceiot

Prealgebra via Python programming - 2018 @pythonlbooks

Introduction to Deep Learning @datascienceiot
Introduction to Deep Learning @datascienceiot

Fundamentals Of Python: Data Structures Github @datascienceiot
Fundamentals Of Python: Data Structures Github @datascienceiot

Data Mining Algorithms in C++ @datascienceiot
Data Mining Algorithms in C++ @datascienceiot

Follow us on Instagram! Where we post coding problems and solutions solved in Python apply your book knowledge to solve probl
Follow us on Instagram! Where we post coding problems and solutions solved in Python apply your book knowledge to solve problems 💪 join now our Instagram https://www.instagram.com/pythonforcoding?r=nametag

Python Deep Learning: Exploring deep learning techniques, neural network architectures and GANs with PyTorch, Keras and Tenso
Python Deep Learning: Exploring deep learning techniques, neural network architectures and GANs with PyTorch, Keras and TensorFlow @datascienceiot

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Mastering SciPy @pythonlbooks

Deep Learning for Search - 2019 @datascienceiot

Python Machine Learning @datascienceiot

Make Your Own Python Text Adventure @pythonlbooks

Python Data Analytics Github @pythonlbooks
Python Data Analytics Github @pythonlbooks

Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning (2019) @pythonlbooks

Text Analytics with Python: A Practitioner's Guide to Natural Language Processing Github @datascienceiot
Text Analytics with Python: A Practitioner's Guide to Natural Language Processing Github @datascienceiot

Derivatives Analytics with Python Book @datascienceiot
Derivatives Analytics with Python Book @datascienceiot

Deep Learning for Computer Vision with Python Github @datascienceiot
Deep Learning for Computer Vision with Python Github @datascienceiot