Математика Дата саентиста
@workakkk - админ @data_analysis_ml - ds https://gosuslugi.ru/snet/67b55bb01a1c5a6fb6ecc946
Show more📈 Analytical overview of Telegram channel Математика Дата саентиста
Channel Математика Дата саентиста (@data_math) in the Russian language segment is an active participant. Currently, the community unites 14 054 subscribers, ranking 9 185 in the Technologies & Applications category and 47 321 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 14 054 subscribers.
According to the latest data from 19 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -52 over the last 30 days and by 3 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 17.50%. Within the first 24 hours after publication, content typically collects 6.82% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 459 views. Within the first day, a publication typically gains 958 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 51.
- Thematic interests: Content is focused on key topics such as llm, программирование, параметр, визуализация, stepik.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“@workakkk - админ
@data_analysis_ml - ds
https://gosuslugi.ru/snet/67b55bb01a1c5a6fb6ecc946”
Thanks to the high frequency of updates (latest data received on 20 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.
# Install bayesnf from PIP into venv:
$ python -m venv pyenv
$ source pyenv/bin/activate
$ python -m pip install -U bayesnf
# Install dependencies for Python 3.10
$ python -m pip install -r requirements.Python3.10.14.txt
📌Лицензирование : Apache 2.0 License.
🟡Документация
🟡Arxiv
🖥GitHub
@ai_machinelearning_big_data
#AI #ML #Predictions #BAYESNF
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