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
Deep Learning by Ian Goodfellow @datascienceiot

A Concise Introduction to Programming in Python, Second Edition @pythonl

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python @datascienceiot

Big Data Analytics Made Easy @datascienceiot

Practical Data Science Cookbook @datascienceiot

Data Science with Python and Dask @datascienceiot

📔Practices of the Python Pro @pythonl

Python: Deeper Insights into Machine Learning @datascienceiot

Python for Programmers: with Big Data and Artificial Intelligence Case Studies @datascienceiot

Practical Web Scraping for Data Science: Best Practices and Examples with Python @pythonl

Bayesian Reasoning and Machine Learning @datascienceiot

Natural Language Annotation for Machine Learning @datascienceiot

Machine Learning and Security — C. Chio, D. Freeman (en) 2018 @datascienceiot

Neural Arithmetic Units Code for Neural Arithmetic Units (ICLR) and Measuring Arithmetic Extrapolation Performance (SEDL|Neur
Neural Arithmetic Units Code for Neural Arithmetic Units (ICLR) and Measuring Arithmetic Extrapolation Performance (SEDL|NeurIPS): https://github.com/AndreasMadsen/stable-nalu Paper : https://openreview.net/forum?id=H1gNOeHKPS @ai_machinelearning_big_data

Deep Learning with Azure — M. Salvaris, D. Dean, W. Tok (en) 2018 @datascienceiot

Big Data Concepts, Theories, and Applications @datascienceiot

Guide to Big Data Applications @datascienceiot

Building Intelligent Systems @datascienceiot

Introduction to Deep Learning Business Applications for Developers @datascienceiot

Advanced Analytics with Spark @datascienceiot