en
Feedback
Data Science

Data Science

Open in Telegram

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

Show more

📈 Analytical overview of Telegram channel Data Science

Channel Data Science (@datascienceiot) is an active participant. Currently, the community unites 41 811 subscribers, ranking 3 226 in the Technologies & Applications category and 15 215 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 41 811 subscribers.

According to the latest data from 28 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -113 over the last 30 days and by -7 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 5.78%. Within the first 24 hours after publication, content typically collects 2.45% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 417 views. Within the first day, a publication typically gains 1 024 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 29 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.

41 811
Subscribers
-724 hours
-637 days
-11330 days
Posts Archive
Artificial Intelligence for Marketing Github @datascienceiot
Artificial Intelligence for Marketing Github @datascienceiot

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

Deep Learning: State of the Art (2020) Book @datascienceiot

Data Analysis with Pandas @datascienceiot

An Introduction to Machine Learning Interpretability Github @datascienceiot
An Introduction to Machine Learning Interpretability Github @datascienceiot

Machine Learning Pocket Reference: Working with Structured Data in Python Github @datascienceiot
Machine Learning Pocket Reference: Working with Structured Data in Python Github @datascienceiot

Learning Pandas Github @datascienceiot
Learning Pandas Github @datascienceiot

Numpy tutorial Github @datascienceiot
Numpy tutorial Github @datascienceiot

Scipy Linear Algebra @datascienceiot

Agile Machine Learning: Effective Machine Learning Inspired by the Agile Manifesto (2019) @datascienceiot

Big Data, Data Mining, and Machine Learning @datascienceiot

Flask Web Development @pythonlbooks

Beginning Apache Spark 2 @datascienceiot

Data Scientists at Work

Deep Learning in Python: Master Data Science and Machine Learning with Modern Neural Networks written in Python @pythonlbooks

Strategic Engineering for Cloud Computing and Big Data Analytics @datascienceiot

Veracity of Big Data @datascienceiot

📚Fresh book by Nassim Taleb Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications https://arxiv.org/abs/2001.10488 @ai_machinelearning_big_data

📚Fresh book by Nassim Taleb Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications https://arxiv.org/abs/2001.10488