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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
Build a Career in Data Science (2020) @datascienceiot

Neural Networks: A Visual Introduction for Beginners by Michael Taylor @datascienceiot

Practical time series analysis: master time series data processing, visualization, and modeling using Python @pythonlbooks

Machine Learning for Algorithmic Trading (2020) @datascienceiot

Linear Algebra and Learning from Data (2019) @datascienceiot

Natural Language Processing Recipes - 2019 Github @datascienceiot
Natural Language Processing Recipes - 2019 Github @datascienceiot

Mastering pandas for Finance Github @datascienceiot
Mastering pandas for Finance Github @datascienceiot

Artificial Intelligence for Big Data Github @datascienceiot
Artificial Intelligence for Big Data Github @datascienceiot

PySpark Recipes Github @datascienceiot
PySpark Recipes Github @datascienceiot

Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python - 2020 Github @datascienceiot
Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python - 2020 Github @datascienceiot

Practical Synthetic Data Generation (2020) Github @datascienceiot
Practical Synthetic Data Generation (2020) Github @datascienceiot

Deep Learning for Coders with fastai and PyTorch (2020) Github @datascienceiot
Deep Learning for Coders with fastai and PyTorch (2020) Github @datascienceiot

Intro to Python for Computer Science and Data Science - 2020 @pythonlbooks

Глубокое обучение без математики. Практика @datascienceiot
Глубокое обучение без математики. Практика @datascienceiot

Advanced Deep Learning with TensorFlow 2 and Keras (2020) @datascienceiot

Practical Natural Language Processing (2020) @datascienceiot

Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data @datascienceiot

Hands-On Data Analysis with Pandas - 2019 @datascienceiot

R Programming: A Step-by-Step Guide for Absolute Beginners (2020) @datascienceiot

Data Science and Analytics with Python @pythonlbooks