Job listings — 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 16 September 2026 and assigned it the closest of 31 fixed categories, at 80% 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 why it has no browse page of its own yet.
Growth
12 measurements spanning 50 days, net -11. 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 2,180–2,203 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
26 Sept 2026, 05:37
2,183
-8
17 Sept 2026, 14:37
2,191
+6
13 Sept 2026, 16:18
2,185
-1
9 Sept 2026, 12:14
2,186
-5
3 Sept 2026, 22:19
2,191
-3
29 Aug 2026, 02:12
2,194
-2
26 Aug 2026, 04:17
2,196
+1
23 Aug 2026, 03:29
2,195
-3
16 Aug 2026, 22:09
2,198
-2
13 Aug 2026, 17:17
2,200
+6
8 Aug 2026, 01:35
2,194
no change
7 Aug 2026, 06:33
2,194
first reading
Engagement
16 posts held, back to 12 April 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pages 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 16 posts for this entry, the most recent from 17 May 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
487 reactions across 15 posts, in 15 distinct kinds. The most used accounts for 34.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
169
34.7%
🔥
109
22.4%
❤
105
21.6%
😁
37
7.60%
✍
15
3.08%
👏
13
2.67%
👀
8
1.64%
🗿
8
1.64%
⚡
5
1.03%
🎉
5
1.03%
💯
4
0.821%
🌚
3
0.616%
🤝
3
0.616%
🎃
2
0.411%
🙏
1
0.205%
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 15 of the 16 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 487 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 12 April 2025 to 17 May 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.
Telegram Stars
Stars received
6
across the posts below
Posts paid on
3
of 16 we hold a reading for · 19%
Most on one post
4
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @DataKatser. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 16 most recent posts we hold for this entry, published 12 April 2025 to 17 May 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Поделюсь хорошими новостями: я вывалился за правую границу графика (8 лет с начала PhD прошло!) и возвращаюсь в группу "обычного риска" по психиатрическим диагнозам и принимаемым лекарствам🥳 Чего и вам советую (лучше, конечно, в левой части графика оставайтесь)!
PS Меня все эти диагнозы, к счастью, обошли стороной, но было, конечно, всякое😓
PPS Диссертацию так и не защитил, но какие наши годы
Источник: https://lucr…
Ищу к себе в команду
Пост от Иры
- Senior DS (LLM Engineer). Автоматизация бизнес-процессов.
- Data TechLead в команду управления данными - развитие Data & AI-платформу и сервисы для домена
- TechLead ML/AI и данных в антифроде
- Owner команды data governance и системного анализа. Улучшение данных на уровне большого домена.
По любым деталям - ко мне в ЛС.
В заголовке резюме или в сообщении, пожалуйста, пишите, кака…
Каминг-аут
Как за последнее время пошутили несколько коллег и знакомых: «Ну когда уже совершишь?» 🙂 Бэйдж, кстати, с конференции industrial++ (но этого года) на которой я еще состою в программном комитете, но уже не принимаю активного участия. Это одна из последних активностей по теме промышленности, что у меня вообще остались. Хотя на доклады я не попал, зато успел на афтерпати, был рад видеть всех знакомых и друзе…
Скоро расскажу, как я сменил промышленность на другую отрасль экономики, но пока делюсь папкой с дружественными каналами! С кем-то знаком лично (и даже вместе учились), кого-то читаю, с кем-то только познакомился, но ребята 🔥 Каналов много, каналы разные, рекомендую, потому что важно расширять кругозор. Тогда можно и бестпрактис приносить в ту же вечно отстающую промышленность, и домен сменить при желании.
Хотите пр…
👨От хакатона до автоматизации флотации: путь в промышленный AI
Дисклеймер: Триумфальное возвращение в рабочий режим! Накопилось много материалов и новостей, но давайте обо всем по порядку.
Сегодня делюсь интервью, собранным в виде статьи на хабр.
О материале:
Как попасть из Бауманки в AI-индустрию, почему важно не просто разработать модель, но и довести её до пузырей в бочке и настоящего результата. Выяснили, поче…
Исследование специалистов по работе с данными — 2025
В прошлом году вышел интересный отчет от DevCrowd по тому, как работают дата-инженеры, аналитики, дата-сайентисты, ML-инженеры. Но, признаюсь, мне не хватило отраслевой специфики и, в частности, информации про промышленность 👨, типа:
• источники знаний
• популярные авторы
• особенности инструментов
• и тд
Ребята из DevCrowd рассказали, что для выделения направлен…
AI/ML/DS в вибродиагностике. Часть 2 — погружение
Часть 1. Продолжаем с Даниилом цикл, посвящённый вибродиагностике роторного оборудования.
⛓️💥Неразрушающий контроль
Вибродиагностика является частью более обширной области неразрушающего контроля (см. ГОСТ Р 56542-2015). Последнее означает, что нам не требуется демонтировать и разбирать оборудование для оценки его технического состояния. При этом, существуют как акт…
Очередной майлстоун в моей "карьере" исследователя: если раньше было 💯 цитирований моего профиля всего, то теперь 💯 цитирований пробила всего лишь одна статья.
Станет постоянной рубрикой: будем вместе отмечать поздравления от scholar.google❤️
Моделирование работы гидроциклона для очистки воды от нефти с помощью ML
Поделюсь интересной статьей с хабра — поддержим коллегу❗️
Отмечу несколько моментов:
✅Согласен с формулировкой "Если разработанное решение решает задачу уже на в полуавтомате 3+, то это уже успех". Называю это иногда "инженерный подход". Сюда же отношу всегда транслируемый мной фокус на решении задачи, а не внедрении ИИ любой ценой. Другими сло…
Доменная экспертиза для DSов в промышленности
🔵Одним из требований (или одной из составлящих) профессии датасайентиста является экспертиза в доменной области. В промышленности это требование имеет еще большую важность из-за большой ответственности (промышленные объекты являются опасными или объектами промышленного риска), сложности технологических процессов и пересечения с разными смежными науками (физика, химия, ме…
📰Чтиво на выходные: что-то помимо машинного обучения в промышленности
Сегодня цикл статей о роли CDO от Reliable ML.
🔘Советы для CDO — концентрированная выжимка из CDO Playbook. В этом посте речь про выстраивание работы, роль CDO, типы CDO и дата-офисы.
🔘Как нанять хорошего CDO — вторая часть выжимки про найм (навыки, мотивацию), уровень полномочий, помощь (свобода, публичная поддержка).
🔘Экономика дата офиса — пост…
👍4❤3🔥2
Showing the 12 most recent of 16 posts we hold for @DataKatser. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
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.
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 16 most recent posts we hold, published 12 April 2025 to 17 May 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.
Forward network
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
Named by 2 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@DataKatser named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@reliable named in 1 post, 8 August 2026 – 8 August 2026
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Data Science Jobs @datascienceml_jobs · 21,227 Telegram ranks this channel #94 of 97 here — alongside 96 others — read 24 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 26 September 2026 — this
entry's latest reading, not the date you are reading this.
“Katser” (@DataKatser), 2,183 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/DataKatser.
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.