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Data Science

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 41 817 subscribers, ranking 3 211 in the Technologies & Applications category and 15 203 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 41 817 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.

41 817
Subscribers
+424 hours
-627 days
-10230 days
Posts Archive
Foundations of Deep Reinforcement Learning (2019) @datascienceiot

Practical Numerical and Scientific Computing with MATLAB® and Python (2020) @datascienceiot

introduction to Modeling and Simulation with MATLAB® and Python @datascienceiot

Data Analysis From Scratch With Python: Beginner Guide using Python, Pandas, NumPy, Scikit-Learn, IPython, TensorFlow and Matplotlib @datascienceiot

🔥Startup Village Livestream’20: "Art of innovation: startup as a masterpiece". May 21-22🔥 Meet the founders of unicorn star
🔥Startup Village Livestream’20: "Art of innovation: startup as a masterpiece". May 21-22🔥 Meet the founders of unicorn startups, accelerators, corporations and investment funds online! 200 speakers, 1000 investors, 4500 startups. 👉 90+ live sessions and 4 event flows; 👉 Talks by tech visionaries & famous entrepreneurs; 👉 Q&A in real time; 👉 Startup pitching contest; 👉 3D tech fair; 👉 Networking & group chats. Participation is FREE! Join now!

Building Chatbots with Python - 2019 @datascienceiot

Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C# - 2019 @pythonl

Computer Simulation: A Foundational Approach Using Python @datascienceiot

Python: Искусственный интеллект, большие данные и облачные вычисления Дейтел П., Дейтел Х. (2020) @pythonlbooks

Data Science - канал на котором ты сможешь узнать о нейронных сетях и их разработке, о математических алгоритмах, передовых т
Data Science - канал на котором ты сможешь узнать о нейронных сетях и их разработке, о математических алгоритмах, передовых технологиях и других фишках Big Data. Также на канале публикуются ваканасии для новичков и профессионалов. Перейти...

Beginning Data Science with Python and Jupyter @datascienceiot

Введение в машинное обучение @datascienceiot
Введение в машинное обучение @datascienceiot

Probability and Statistics for Data Science (2019) Github @datascienceiot
Probability and Statistics for Data Science (2019) Github @datascienceiot

Python ® Machine Learning - 2019 Github @datascienceiot
Python ® Machine Learning - 2019 Github @datascienceiot

Google Cloud Platform in Action Github @datascienceiot
Google Cloud Platform in Action Github @datascienceiot

Data Analysis and Visualization Using Python - 2018 Github @datascienceiot
Data Analysis and Visualization Using Python - 2018 Github @datascienceiot

The Enterprise Big Data Lake (2019) Github @datascienceiot
The Enterprise Big Data Lake (2019) Github @datascienceiot

6 Free Data Mining and Machine Learning eBooks - DZone Big Data https://dzone.com/articles/6-free-data-mining-and-machine-learning-ebooks

Mastering Large Datasets with Python: Parallelize and Distribute Your Python Code (2020) @pythonlbooks

Примените машинное обучение для предсказания фондового рынка. Создайте модель, используя наши метаданные и шаблоны кода на Py
Примените машинное обучение для предсказания фондового рынка. Создайте модель, используя наши метаданные и шаблоны кода на Python. Участвуйте в розыгрыше полумиллиона рублей. Подробнее: https://vk.com/quantnetrussia https://quantnet.ai/