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по всем вопросам @haarrp @itchannels_telegram - 🔥 все ит каналы @ai_machinelearning_big_data -ML @ArtificialIntelligencedl -AI @datascienceiot - 📚 @pythonlbooks РКН: clck.ru/3FmxmM

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MachinelearningNetwork:MachinelearningRussia10 243Technologies & Applications2 219

📈 Analytical overview of Telegram channel Python/ django

Channel Python/ django (@pythonl) in the Russian language segment is an active participant. Currently, the community unites 59 843 subscribers, ranking 2 219 in the Technologies & Applications category and 10 243 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 59 843 subscribers.

According to the latest data from 20 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -524 over the last 30 days and by -24 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 8.88%. Within the first 24 hours after publication, content typically collects 3.43% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 5 317 views. Within the first day, a publication typically gains 2 052 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 28.
  • Thematic interests: Content is focused on key topics such as github, claude, контекст, архитектура, api.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“по всем вопросам @haarrp @itchannels_telegram - 🔥 все ит каналы @ai_machinelearning_big_data -ML @ArtificialIntelligencedl -AI @datascienceiot - 📚 @pythonlbooks РКН: clck.ru/3Fmxm...”

Thanks to the high frequency of updates (latest data received on 21 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.

59 843
Subscribers
-2424 hours
-1227 days
-52430 days
Posts Archive
Python/ django
Python/ django
59 836

Python/ django
Python/ django
59 836
Neural Networks from Scratch - Coding a Layer A beginner’s guide to understanding the inner workings of Deep Learning https://morioh.com/p/fb1b9f5a52bc Video Part 1: https://www.youtube.com/watch?v=Wo5dMEP_BbI Video Part 2: https://www.youtube.com/watch?v=lGLto9Xd7bU

Python/ django
Python/ django
59 836
Connecting Flask and Nginx with Docker https://morioh.com/p/b4d97538df90

Python/ django
Python/ django
59 836
Announcing PyCaret 1.0.0 An open source low-code machine learning library in Python. PyCaret allows you to go from preparing data to deploying models within seconds from your choice of notebook environment. https://towardsdatascience.com/announcing-pycaret-an-open-source-low-code-machine-learning-library-in-python-4a1f1aad8d46 Habr RU : https://habr.com/ru/company/otus/blog/497770/ Github: https://github.com/pycaret/pycaret Guide: https://pycaret.org/guide/

Python/ django
Python/ django
59 836
Implement Face Detection from Image and Video with Python https://morioh.com/p/108652f1547a

Python/ django
Python/ django
59 836
How to Develop Voting Ensembles With Python https://machinelearningmastery.com/voting-ensembles-with-python/

Python/ django
Python/ django
59 836
Web Scraping with Python https://morioh.com/p/284807096613

Python/ django
Python/ django
59 836
Quick Domain-Specific Languages in Python with textX https://tomassetti.me/quick-domain-specific-languages-in-python-with-textx/

Python/ django
Python/ django
59 836
Nevergrad, an evolutionary optimization platform, adds new key features Facebook AI’s open source Python3 library for derivative-free and evolutionary optimization. https://ai.facebook.com/blog/nevergrad-an-evolutionary-optimization-platform-adds-new-key-features/ GitHub: https://github.com/facebookresearch/nevergrad Documentation: https://facebookresearch.github.io/nevergrad/index.html

Python/ django
Python/ django
59 836
Combining Data in Pandas With merge(), .join(), and concat() https://realpython.com/pandas-merge-join-and-concat/

Python/ django
Python/ django
59 836
Научи нейросеть узнавать объекты с первого раза. Приходи на открытый урок по Нейросетям на Python https://otus.pw/BW0O/ 14 ап
Научи нейросеть узнавать объекты с первого раза. Приходи на открытый урок по Нейросетям на Python https://otus.pw/BW0O/ 14 апреля в 20:00 Михаил Степанов, эксперт по машинному обучению из Jet Infosystems, проведет занятие по Triplet loss. Что будем делать: * Научимся работать с tensorflow datasets * Рассмотрим проблему one-shot learning, metric learning * Разберемся, что такое siamese networks и triplet loss * Обучим нейросеть, способную с первого раза узнавать объекты Требуется знание Python и математики. Проходи вступительный тест и записывайся в группу, пока действуют самые большие скидки!

Python/ django
Python/ django
59 836
Neural Networks from Scratch - P.1 Intro and Neuron Code https://morioh.com/p/d3398c5b6c25

Python/ django
Python/ django
59 836

Python/ django
Python/ django
59 836
10+ Python Tips and Tricks You Should Know in 2020 https://morioh.com/p/7430d87868f7

Python/ django
Python/ django
59 836
Using Python to Check for File Changes in Excel https://pybit.es/using-python-to-check-for-file-changes-in-excel.html

Python/ django
Python/ django
59 836
Selenium Webdriver using Python: Tutorial with Examples https://morioh.com/p/4aaa28813caf

Python/ django
Python/ django
59 836

Python/ django
Python/ django
59 836
How to Make an Instagram Bot With Python and InstaPy https://realpython.com/instagram-bot-python-instapy/

Python/ django
Python/ django
59 836
Django Social Login Authentication Example https://morioh.com/p/185f50b2f195

Python/ django
Python/ django
59 836