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Data Science

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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
Intro to Python for Computer Science and Data Science (2019) @datascienceiot

Efficient Processing of Deep Neural Networks @datascienceiot

Programming Algorithms. A comprehensive guide to writing efficient programs with examples in Lisp @datascienceiot

А вы знаете, что самые высокооплачиваемые вакансии на удаленке это IT & Digital? Канал @hiddengurus ежедневно подготавливает
А вы знаете, что самые высокооплачиваемые вакансии на удаленке это IT & Digital? Канал @hiddengurus ежедневно подготавливает выборку таких топовых позиций специально для вас. После подписки вы получите: - Свежие вакансии прямиком от работодателей. - Возможность принять участие в крутых проектах из США, Европы, РФ и Латинской Америки. - Возможность прокачать свой скилл, и стать настоящим гуру. - Царскую ЗП до 10000$/месяц. - Шанс работать из любой точки мира, когда удобно вам! Подписывайтесь на канал @hiddengurus - это шанс изменить вашу жизнь! Подписаться

Data Visualisation: A Handbook for Data Driven Design @datascienceiot

Deep Learning Architectures - 2020 @datascienceiot

Histogram-based Outlier Score (HBOS): A fastUnsupervised Anomaly Detection @datascienceiot

Data Visualization with Python and JavaScript Github @datascienceiot
Data Visualization with Python and JavaScript Github @datascienceiot

Machine Learning For Absolute Beginners Github @datascienceiot
Machine Learning For Absolute Beginners Github @datascienceiot

Convolutional Neural Networks in Python Github @datascienceiot
Convolutional Neural Networks in Python Github @datascienceiot

Practical Artificial Intelligence - 2018 Github @datascienceiot
Practical Artificial Intelligence - 2018 Github @datascienceiot

Kubernetes Operators (2020) Github @datascienceiot
Kubernetes Operators (2020) Github @datascienceiot

Эволюционные нейросети на языке Python - 2020 Github @datascienceiot
Эволюционные нейросети на языке Python - 2020 Github @datascienceiot

Probabilistic Data Structures and Algorithms for Big Data Applications (2019) Github @datascienceiot
Probabilistic Data Structures and Algorithms for Big Data Applications (2019) Github @datascienceiot

Deep Learning with TensorFlow 2 and Keras (2019) @datascienceiot

The Practitioner's Guide to Graph Data (2020) @datascienceiot

Semantic Bottleneck Layers: Quantifying and Improving Inspectability of Deep Representations @datascienceiot

Foundations of Libvirt Development: How to Set Up and Maintain a Virtual Machine Environment with Python @datascienceiot

Data Structures and Algorithms in C++ (2011) @datascienceiot