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Channel

Small Data Science for Russian Adventurers

@smalldatascience

On this record: Growth · Engagement · Reactions · Posts · Polls · Citations · Cite this entry

11,540subscribers

-5 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001421901024
TypeChannel
Username@smalldatascience
Created17 December 2019measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live14 August 2026
Measurements held10
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/smalldatascience

Growth

11,53711,54511,5416 August 2026 — 11,545 subscribers6 August 2026 — 11,545 subscribers7 August 2026 — 11,543 subscribers8 August 2026 — 11,542 subscribers9 August 2026 — 11,540 subscribers10 August 2026 — 11,541 subscribers11 August 2026 — 11,537 subscribers12 August 2026 — 11,539 subscribers13 August 2026 — 11,543 subscribers14 August 2026 — 11,540 subscribers11,5406 August 202614 August 2026
10 measurements spanning 8 days, net -5. 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 11,536–11,546 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 12:5611,540-3
13 Aug 2026, 05:1511,543+4
12 Aug 2026, 07:3111,539+2
11 Aug 2026, 07:4111,537-4
10 Aug 2026, 07:4611,541+1
9 Aug 2026, 06:0011,540-2
8 Aug 2026, 06:4011,542-1
7 Aug 2026, 04:1611,543-2
6 Aug 2026, 10:0711,545no change
6 Aug 2026, 09:5011,545first reading

Engagement

19 posts held, back to 14 April 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 16 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
34.8%
avg views ÷ 11,540 subscribers
Avg views / post
4,020
1 post measured
Reaction rate
1.92%
reactions ÷ views · ER floor
Posts in window
1
of 19 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 22 July 2026
Posts held19 (14 April 202522 July 2026)
Views total4,020
Reactions total77
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Aug 2026, 04:02 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

2,030 reactions across 19 posts, in 27 distinct kinds. The most used accounts for 34.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥69934.4%
52025.6%
👍34817.1%
🤯1447.09%
🎄753.69%
😢532.61%
😁351.72%
💯301.48%
🤔190.936%
❤‍🔥150.739%
🙈150.739%
💩120.591%
👎100.493%
🥴100.493%
👏80.394%
🍾60.296%
😍50.246%
🙏50.246%
🤣50.246%
😱40.197%
7 further kinds120.591%

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 19 of the 19 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 2,030reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 14 April 2025 to 22 July 2026, 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

22 Jul 2026, 12:50 UTC≈4,020 views77 reactionsread 13 August 2026
Photo

#ссылка Блог Кристофа Мольнара в основном про решение табличных задач машинного обучения. В последнем посте (кстати, опубликован час назад) описаны тренды в табличных фундаментальных моделях (tabular foundation models) по анализу докладов конференции ICML. Вообще, автор пишет книгу на эту тему. https://mindfulmodeler.substack.com/

33🔥26👍18

31 Mar 2026, 10:21 UTC≈8,110 views73 reactionsread 13 August 2026
Poll

Интересное о терминах: если что-то искать (например, в интернете), а внезапно найти другое, но очень полезное... то это называется термином, связанным с

  1. отелем "Калифорния"34%
  2. страной Гондурас14%
  3. островом Шри-Ланка10%
  4. горой Эверест7%
  5. пирамидой Хеопса15%
  6. городом Воронежем20%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

🤯25🔥23👍9🤣5🥴4🤔32💩2

13 Mar 2026, 08:18 UTC≈11,300 views186 reactionsread 13 August 2026
Photo

#поворчу Очень давно не был в диссоветах, а за последние полгода поприсутствовал примерно на десяти защитах в разных местах - и как научный руководитель, и как оппонент. Остро ощутил: защита осталась забюрократизированным, не приносящим радости ритуалом. Казалось бы, это «финишная прямая» исследователя. Но вместо того, чтобы «пересечь ленту финишёром с гордо поднятыми руками», соискатель бегает и собирает бумажки (и

🤯79😢53💯30🙈15🔥4🥱3💩1🥴1

26 Jan 2026, 14:01 UTC≈10,600 views57 reactionsread 13 August 2026
Photo

#новости В выходные в Москве и Питере прошла Data Ёлка 2025, на которой были интересные доклады про итоги года в разных областях науки о данных. Можно посмотреть запись трансляции. Некоторые спикеры выкладывают в своих каналах материалы, например Владимир Байкалов из нашей научной группы. Саша Пославский провёл награждение соревнования на самом большом датасете для рекомендации коротких видео. Также была запись подка

🔥3318👍6

10 Jan 2026, 18:40 UTC≈13,300 views100 reactionsread 13 August 2026
Photo

#визуализация Ещё одна электронная книга (небольшая) с визуализацией концепций ML. Сделано аккуратно: приводятся формулы, код и доводится до красивой картинки (или видео). Правда, всего 4 главы: оптимизация, кластеризация, линейные модели и нейросети. Материал "начального уровня" (но удобно, что он тут собран). https://ml-visualized.com/

👍58🔥289🙏3🥴2

31 Dec 2025, 12:42 UTC≈11,300 views265 reactionsread 13 August 2026
Photo

Дорогие подписчики и единомышленники канала, с Новым годом! 🎄 Желаю в 2026м - смелых (и авантюрных;) планов, удачи в их реализации и удовольствия от их результатов!

156🎄74🔥24🍾6👍5

19 Nov 2025, 11:49 UTC≈14,700 views119 reactionsread 13 August 2026
Photo

#анонс Завтра выступлю на ФКН ВШЭ с лекцией "Удовольствие от данных" про соревновательный анализ данных. Весь материал исключительно о собственном опыте (немного в ретро-стиле, зато от души). Примеры случайных слайдов – на картинке. Кому удобно и хочется – приходите! Подробности здесь (заодно порекламирую канал Никиты Зелинского – он часто постит то, что я бы хотел, но не хватает времени).

👍53🔥3729

12 Nov 2025, 11:48 UTC≈16,600 views210 reactionsread 13 August 2026
Photo

#новости В МГУ открывают новый "малый" факультет - Искусственного Интеллекта. Набор уже в следующем году. Как я понимаю, факультет стоит на трёх китах: AIRI, институт ИИ МГУ и фонд "Интеллект". Деканом будет генеральный директор AIRI Иван Оселедец (вчера он был представлен на учёном совете). Ректор МГУ уже давно анонсировал запуск факультета ИИ. В частности, говорил об интеграции в него суперкомпьютера "МГУ-270".

105👍56🔥28🤔8👎7😁2😨2🐳1

31 Oct 2025, 07:04 UTC≈12,300 views81 reactionsread 13 August 2026
Photo

#видео Значения Шепли На модельном примере упрощённой игры ЧГК показал, как вычисляются значения Шепли и справедливо разделяется выигрыш. Пример открывает серию возможных задач - меняя правила игры, получаем разные значения Шепли, не вегда они соответсвуют нашей интуиции. в ВК-видео https://vkvideo.ru/video-232735712_456239019 на Дзене https://dzen.ru/video/watch/690202ecac78f246b0a0c86a?share_to=link

🔥50👍1813

28 Oct 2025, 15:22 UTC≈9,620 views58 reactionsread 13 August 2026
Photo

#интересно Несмотря на наличие LLM, во многих вопросно-ответных сервисах жизнь теплится. Например, в разделе «Академия» на StackExchange задаются вопросы, связанные с исследованиями и около них. Во многих обсуждениях разыгрываются целые жизненные трагедии – на их основе получился бы отличный фильм про изнанку научного мира. Один из последних постов – молодого человека мучает совесть из-за того, что он опубликовал и

25😁17👍8🤔5🔥3

27 Oct 2025, 11:24 UTC≈9,220 views107 reactionsread 13 August 2026
Photo

#книга Факур М., Груздев А.В. «Причинно-следственный анализ для смелых и честных» Книга по теме, которая активно проникает в образовательные DS-программы (но почему-то не во все). Написана довольно понятным языком, всё поясняется на простых датасетах и рисунках, в книге много мемасиков и примеров. Но читать её всё-таки лучше со знаниями теории вероятностей (там сходу условные матожидания, хотя формул не так много).

🔥7021😁8👍5💩3

2 Oct 2025, 08:12 UTC≈10,600 views45 reactionsread 13 August 2026
Photo

#видео Ещё немного короткого научпопа: как предсказывать без ошибок и знаний. Первая часть видео очень простая - "для школьников", вторая больше про ML. Парадокс футбольного оракула в VK-видео https://vkvideo.ru/video-232735712_456239018 на Дзене https://dzen.ru/video/watch/68dd98bdf70604051dc59350 (за картинку спасибо Кандинскому)

🔥25👍95😁5🥴1

Showing the 12 most recent of 19 posts we hold for @smalldatascience. 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.

Polls

The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.

31 Mar 2026, 10:21 UTCAnonymous Quiz1,380 voters approx.

Интересное о терминах: если что-то искать (например, в интернете), а внезапно найти другое, но очень полезное... то это называется термином, связанным с

  1. отелем "Калифорния"34%
  2. страной Гондурас14%
  3. островом Шри-Ланка10%
  4. горой Эверест7%
  5. пирамидой Хеопса15%
  6. городом Воронежем20%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

Percentages only — there are no per-option vote counts here, because Telegram publishes none.The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.

The shares need not add up to 100.Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.

Read from the 19 most recent posts we hold, published 14 April 2025 to 22 July 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.

Citation-graph rank

Citation-graph rank — 962,797 of 1,345,403entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

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 14 August 2026 — this entry's latest reading, not the date you are reading this.

“Small Data Science for Russian Adventurers” (@smalldatascience), 11,540 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/smalldatascience.

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.