Channel
@mashin_learning_tv
On this record: Growth · Engagement · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry
1,116subscribers
-1 since we began measuring on 16 September 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001864933695 |
|---|---|
| Type | Channel |
| Username | @mashin_learning_tv |
| Created | Between 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 16 September 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/mashin_learning_tv |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 01:19 | 1,116 | -1 |
| 16 Sept 2026, 14:22 | 1,117 | no change |
| 16 Sept 2026, 13:47 | 1,117 | first reading |
14 posts held, back to 30 December 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 14 posts for this entry, the most recent from 17 October 2025. An engagement rate over an empty window would be a number about nothing.
232 reactions across 14 posts, in 13 distinct kinds. The most used accounts for 32.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 75 | 32.3% | |
| ❤ | 74 | 31.9% | |
| 😁 | 35 | 15.1% | |
| 👍 | 16 | 6.90% | |
| 🎉 | 13 | 5.60% | |
| ❤🔥 | 4 | 1.72% | |
| 🆒 | 4 | 1.72% | |
| 🤣 | 3 | 1.29% | |
| 🥴 | 3 | 1.29% | |
| 🥰 | 2 | 0.862% | |
| 👎 | 1 | 0.431% | |
| 💩 | 1 | 0.431% | |
| 🤔 | 1 | 0.431% |
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 14 of the 14 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 232 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 14 most recent posts we hold, published 30 December 2024 to 17 October 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @mashin_learning_tv. 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 14 most recent posts we hold for this entry, published 30 December 2024 to 17 October 2025. 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.
✨На конфе было большое количество трэков и соответствующих дедлайнов. Я сабмитила эбстракты и делала withdraw, пока не наступил последний дедлайн, — Late Breaking Results — и капс локом в голове "Маша, или сейчас пишем, или никогда". Где-то за неделю я собрала нужные инсайты и соответствующие ссылки и за 3 для написала. ✨Далее меня очень позабавило, что я фактически no name для этого community, но они написали "…
❤15🔥8
/AIED: part1/ Уже пора уезжать на следующую конференцию, а я еще не рассказала про две предыдущие:) Мое вливание в мир DL из экономики началось примерно тогда, когда я увидела на Kaggle вот эту сореву и поняла, что этой задачей я занималась бы с горящими глазами, а не тем, что я делаю на работе. Помню примерно тогда же у меня был one-to-one с начальником, где он недоумевал, почему я не проявляю достаточно инициатив…
🔥9❤2🥰2
/Will It Still Be True Tomorrow? Multilingual Evergreen Question Classification to Improve Trustworthy QA/ Одна из задач, которой мы занимаемся в команде, - задача адаптивного ретривала. Замечали когда-нибудь, когда использовали ChatGPT, "searching the Web"? Когда и как алгоритм решает, что можно положиться исключительно на параметрические знания, а когда необходимо поискать релевантный контекст? Одним из возможных…
🔥13❤🔥4🆒4❤1
Photo, posted without a caption
👍1🤔1
How much did your paper co-authors work? They didn't work et al. (c) Maria Ulyanova
😁16🔥6🤣3❤1
/Можно ли использовать галлюцинации с пользой? Разбираемся/ Мои коллеги разработали новый метод - 🔍Through the Looking Glass (TLG) - который позволяет детектить странные картинки. Пингвины, собирающие бананы? Воробей, солирующий на рок-концерте? Снеговик в пустыне? Или тень от кошки, которая вдруг стала собачьей? Все это кажется нам странным, хотя каждая часть по отдельности выглядит нормально. Мы, люди, улавлива…
🔥12❤5
как привлечь зумеров)
😁19❤3🥴3👎1💩1
Буду рада, если поддержите нас и поставите Upvote ⬆️ на HuggingFace! 💥 https://huggingface.co/papers/2502.14502
🔥9
/How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?/ Long time no see! Но как не вернуться и не рассказать про собственную статью) Первую статью, которую опубликовали в Core A, где ты один из первых авторов, и которую писала в ночь перед дедлайном до 5 утра. Незабываемые все ощущения, особенно рада, что хвалила себя и праздновала сразу после отправки и до вердикта, потому что хвалить надо за пр…
🔥9👍2
Пока радость в моменте, чуть позже про саму статью: Dear Maria Lysyuk, Congratulations! We are delighted to inform you that your submission to NAACL 2025, How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?, has been accepted to the NAACL Findings.
❤19🎉13👍4
/AI & лингвистика & нейронауки/ Наткнулась на интервью трех ученых из MIT, которые работают на пересечении лингвистики, нейронаук и компьютерных наук. Каждый из них закончил одно из соответствующих PhD. Показались нетривиальными направления исследований, которыми они занимаются: 🔺 Правда ли что язык связан с мышлением? Если это так, то соответствующие участки в мозге будут активироваться даже при выполнении не лин…
👍8❤4
/Book challenge'2025/ Посмотрела видео у Саши Митрошиной, что ей дал challenge 52 книг в год. Вынесу из видео то, что понравилось мне, и сама решила публично закоммититься на 30 книг в 2025. Зачем? Любой игровой формат добавляет в жизнь осмысленность, плюс у меня хромает дисциплинированность и системность, хочется ее прокачать. Почему 30? "Важно задать себе адекватный темп и с собой договориться". Мне кажется, мн…
🔥9❤2👍1
Showing the 12 most recent of 14 posts we hold for @mashin_learning_tv. 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.
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.
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.
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.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“Машин лернинг” (@mashin_learning_tv), 1,116 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/mashin_learning_tv.
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.