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Channel

Data Science 🧑‍💻

@datascience_russia

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · Reactions · Posts · Citations · Cite this entry

897subscribers

-10 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001391752527
TypeChannel
Username@datascience_russia
CreatedBetween 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live4 November 2026
Measurements held9
Confirmed unchanged1 time, most recently 4 November 2026
On Telegramt.me/datascience_russia

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 19 September 2026 and assigned it the closest of 31 fixed categories, at 85% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 1 other registered channel. This entry also sits inside a group of 3 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@datascience_russia/244 · this entry15 Mar 2024, 05:09 UTC@CyberMindFlowAI/22815 Mar 2024, 06:54 UTC1.001.8 hours
@datascience_russia/245 · this entry31 Mar 2024, 15:53 UTC@CyberMindFlowAI/66031 Mar 2024, 17:08 UTC1.0075 minutes
@datascience_russia/247 · this entry2 Apr 2024, 17:26 UTC@CyberMindFlowAI/7132 Apr 2024, 20:18 UTC1.002.9 hours
@datascience_russia/252 · this entry11 Jun 2024, 09:27 UTC@CyberMindFlowAI/88711 Jun 2024, 11:54 UTC1.002.5 hours
@datascience_russia/254 · this entry11 Jun 2024, 18:38 UTC@CyberMindFlowAI/88911 Jun 2024, 21:04 UTC1.002.4 hours
@datascience_russia/256 · this entry16 Jun 2024, 19:29 UTC@CyberMindFlowAI/89116 Jun 2024, 21:29 UTC1.002.0 hours
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@CyberMindFlowAI7 (7/7 hand-verifiable sample passed)1.002.4 hoursthis entry (7–0)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.

“Published first” means first in this corpus. We hold 18 comparable posts for this entry, running 30 January 2024 to 31 August 2025. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 3 channels, the one whose matching posts we hold earliest is @datascience_russia — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_source, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Channels linked by matching posts

This channel is in a group of 3 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

8979079027 August 2026 — 907 subscribers8 August 2026 — 907 subscribers24 August 2026 — 905 subscribers9 September 2026 — 907 subscribers18 September 2026 — 904 subscribers2 October 2026 — 902 subscribers13 October 2026 — 903 subscribers27 October 2026 — 901 subscribers4 November 2026 — 897 subscribers7 August 20264 November 2026
9 measurements spanning 89 days, net -10. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 896–909 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
4 Nov 2026, 14:30897-4
27 Oct 2026, 15:56901-2
13 Oct 2026, 12:56903+1
2 Oct 2026, 21:37902-2
18 Sept 2026, 17:00904-3
9 Sept 2026, 16:40907+2
24 Aug 2026, 03:25905-2
8 Aug 2026, 02:48907no change
7 Aug 2026, 04:00907first reading

Engagement

20 posts held, back to 29 January 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 18 November 2025. An engagement rate over an empty window would be a number about nothing.

Reaction mix

15 reactions across 7 posts, in 4 distinct kinds. The most used accounts for 46.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍746.7%
❤426.7%
🔥320.0%
👌16.67%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 7 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 15 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 29 January 2024 to 18 November 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

18 Nov 2025, 09:06 UTC667 views1 reactionsread 7 August 2026

📖 The Little Book of Deep Learning Книжка-шпаргалка для быстрой подготовки к собеседованиям по DL. Скачать

👍1

31 Aug 2025, 10:12 UTC893 views1 reactionsread 7 August 2026

ML-генерация шрифтов #почитать История о том, как я с нуля осваивал создание генеративных моделей МО, попутно обучая компьютер создавать шрифты. Да, настоящие типографские шрифты, состоящие из набора заглавных глифов. Созданная мной модель получает на входе описание шрифта и создаёт на выходе файл с их готовым набором. Читать статью

👍1

25 Aug 2025, 14:50 UTC685 viewsread 7 August 2026

Вопросы на собеседовании ML Team Lead #почитать Если вы читаете это, значит, вы, как и я когда‑то, собираетесь пройти собеседование на позицию ML Team Lead. Или возможно, вы просто интересуетесь тем, что происходит по ту сторону баррикад. В любом случае, давайте поговорим о том, какие вопросы могут задать на таком собеседовании, и как на них отвечать так, чтобы у интервьюеров не осталось сомнений в вашей компетенци…

23 Apr 2025, 14:09 UTC804 viewsread 7 August 2026

Дообучаем языковую модель GPT2 с помощью Torch #почитать В качестве данных я возьму dataset QuyenAnhDE/Diseases_Symptoms с Huggiface. Этот dataset представляет собой небольшой (400 строк) набор болезней, их симптомов и лечение. Я буду использовать только заболевание и его симптомы. То есть на вход модели будет подаваться заболевание, на выходе модель должна написать симптомы. Вы можете использовать обратную логику …

14 Mar 2025, 06:10 UTC756 viewsread 7 August 2026

▫️ Intuitive SQL for Data Analytics #посмотреть 11 часов теории и практики (PostgreSQL) - freeCodeCamp. Смотреть на YouTube ⏱️11 часов

13 Mar 2025, 11:00 UTC595 views4 reactionsread 7 August 2026

Тестируем LLM для русского языка: Какие модели справятся с вашими задачами #почитать YandexGPT: Показала высокую связность и грамматическую правильность текста. Текст был логичным, стилистически правильным и без ошибок. Модель не использовала вставки английских слов, что сделало её результат почти идеальным для русскоязычных проектов (2 балла за выполнение). Saiga-Mistral-7b-Lora: Также показала отличные результат…

❤4

13 Mar 2025, 07:49 UTC486 viewsread 7 August 2026

Мультимодальные модели тотально страдают селективным восприятием Проводя свои текущие исследования для задач сегментации и распознавания объектов на изображениях, я задал простой вопрос многим мультимодальным моделям с целью оценить их способности к интерпретации деталей изображения. Результат был, мягко говоря, странным. С одной стороны, общее описание простой, на первый взгляд, картинки радует подробным и содержа…

9 Jan 2025, 11:40 UTC613 viewsread 7 August 2026
Photo

Создаем воспоминания. Осваиваем FLUX, LoRA и ComfyUI Разбираюсь на праздниках с дообучением моделей для генерации изображений. Было интересно, насколько сложно дообучить модель для генерации изображений по тексту в домашних условиях, сколько нужно обучающих данных и как затем генерировать качественные фотографии и иллюстрации. Чтобы через время не забыть про особенности процесса и как-то его зафиксировать, решил по…

1 Oct 2024, 18:45 UTC821 views2 reactionsread 7 August 2026

Вкатываемся в Machine Learning с нуля за ноль рублей Подробный гайд на тему того, как можно изучать Machine Learning самостоятельно, не тратя деньги на платные курсы. Читать статью

👍2

16 Jun 2024, 19:29 UTC≈1,170 viewsread 7 August 2026

ClickHouse: полезные лайфхаки ClickHouse - это колоночная СУБД для OLAP (online-analytical processing). Большинство аналитиков, которых я знаю, в восторге от ClickHouse, хотя его администрирование имеет свои нюансы и подводные камни. В этой статье я расскажу, что такое ClickHouse и почему я считаю его идеально подходящим мощным инструментом для аналитики, а также поделюсь tips & tricks из моего опыта. Поехали. Чи…

11 Jun 2024, 18:38 UTC909 viewsread 7 August 2026

MLOps. Зачем он нужен и как с ним работать? Обзор полезных инструментов MLOps — это ответвление от DevOps, ряд практик и инструментов, характерных для ML-сферы. По ссылке гайд, рассказывающий о том, что это такое и зачем это нужно.

11 Jun 2024, 09:27 UTC555 views3 reactionsread 7 August 2026
Video

VRT: A Video Restoration Transformer Github: https://github.com/jingyunliang/vrt Paper: https://arxiv.org/abs/2201.12288

🔥3

Showing the 12 most recent of 20 posts we hold for @datascience_russia. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Mentions

Names

Channels on the register whose handles appear in this channel's posts.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 4 November 2026 — this entry's latest reading, not the date you are reading this.

“Data Science 🧑‍💻” (@datascience_russia), 897 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/datascience_russia.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.