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 41 823 subscribers, ranking 3 222 in the Technologies & Applications category and 15 276 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 41 823 subscribers.

According to the latest data from 25 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -111 over the last 30 days and by -6 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.17%. Within the first 24 hours after publication, content typically collects 2.48% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 579 views. Within the first day, a publication typically gains 1 037 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 26 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.

41 823
Subscribers
-624 hours
-707 days
-11130 days
Posts Archive
R and Python for oceanographers ⬇️ Book @datascienceiot
R and Python for oceanographers ⬇️ Book @datascienceiot

Hands-On Python Natural Language Processing - 2020 📖 Github @datascienceiot
Hands-On Python Natural Language Processing - 2020 📖 Github @datascienceiot

Genomics in the Cloud: Using Docker, GATK, and WDL in Terra (2021) Github @datascienceiot
Genomics in the Cloud: Using Docker, GATK, and WDL in Terra (2021) Github @datascienceiot

Python for Algorithmic Trading: From Idea to Cloud Deployment Yves Hilpisch (2021) ⬇️ Download @datascienceiot
Python for Algorithmic Trading: From Idea to Cloud Deployment Yves Hilpisch (2021) ⬇️ Download @datascienceiot

Python Data Analysis, Third Edition - 2021 📖 Book @datascienceiot
Python Data Analysis, Third Edition - 2021 📖 Book @datascienceiot

Ultimate Step by Step Guide to Machine Learning Using Python - 2020 @datascienceiot

📘 D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions Github: https://github.com/d2l-ai/d2l-en Book: https://d2l.ai/ Paper: https://arxiv.org/abs/2106.11342v1 @ai_machinelearning_big_data

Data Mining. Practical Machine Learning Tools and Techniques, Fourth Edition @datascienceiot

Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection - 2019 @datascienceiot

Math for Programmers, Version 10 - 2020 @datascienceiot

Beginning Machine Learning in the Browser (2021) @datascienceiot

Deep Learning. A Visual Apporoach @datascienceiot

Hands-On Simulation Modeling with Python - 2020 @datascienceiot

Applied Natural Language Processing in the Enterprise @datascienceiot

Advanced Analytics in Power BI with R and Python: Ingesting,Transforming, Visualizing - 2020 @datascienceiot

Probabilistic Deep Learning (2020) @datascienceiot

Representation Learning for Natural Language Processing (2020) @datascienceiot

Python Bootcamp: Exercises and Projects (2021) ⬇️ Download @datascienceiot
Python Bootcamp: Exercises and Projects (2021) ⬇️ Download @datascienceiot

Python Machine Learning. Scikit-Learn and TensorFlow @datascienceiot

Python Continuous Integration and Delivery: A Concise Guide with Examples @datascienceiot