Channel
@Practical_ML_Conf
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
182subscribers
+2 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002815546493 |
|---|---|
| Type | Channel |
| Username | @Practical_ML_Conf |
| Description | Регистрация на Practical ML Conf 2026 открыта: https://pmlconf.yandex.ru/2026/ |
| Created | Between 1 June 2025 and 30 September 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 3 |
| On Telegram | t.me/Practical_ML_Conf |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 08:03 | 182 | no change |
| 7 Aug 2026, 06:20 | 182 | +2 |
| 6 Aug 2026, 07:32 | 180 | first reading |
6 posts held, back to 24 June 2026 — 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 pageof 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 6 posts for this entry, the most recent from 10 July 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 7 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
74 reactions across 6 posts, in 9 distinct kinds. The most used accounts for 36.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 27 | 36.5% | |
| 🔥 | 18 | 24.3% | |
| ❤🔥 | 11 | 14.9% | |
| 👍 | 8 | 10.8% | |
| 🙏 | 5 | 6.76% | |
| 🤩 | 2 | 2.70% | |
| 👏 | 1 | 1.35% | |
| 😍 | 1 | 1.35% | |
| 🤯 | 1 | 1.35% |
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 6 of the 6 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 74reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 24 June 2026 to 10 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.
Последний трек в нашей серии, но точно не последний по значимости 📆 Сегодня знакомим вас с программным комитетом Speech: ASR, TTS, аудио-модели, production-инференс и всё, что связано с речевыми технологиями. Подписывайтесь: 🔗 @Practical_ML_Conf
❤4👍3🔥3
В прошлый раз искали доклады в Рио, а теперь зовём гостей из Сеула и вас 🩵 🔳 Регистрируйтесь по ссылке — количество офлайн-мест ограничено. Подписывайтесь: 🔗 @Practical_ML_Conf
❤5❤🔥3🔥3👍1🤩1🤯1
Рекомендательные системы окружают нас каждый день — от маркетплейсов до стриминговых сервисов 🐚 Знакомим вас с программным комитетом RecSys на Practical ML Conf. Среди участников ПК — Николай Савушкин, автор канала Свет из чёрного ящика, где он рассказывает о внедрении рекомендательных технологий в экосистему Яндекса. Подписывайтесь: 🔗 @Practical_ML_Conf
❤3❤🔥3🔥3
Хороший ML не заканчивается на обучении модели 🕹 Сегодня знакомим вас с программным комитетом трека MLOps — экспертов, которые отбирают лучшие доклады о внедрении, эксплуатации и развитии ML-систем. Подписывайтесь: 🔗 @Practical_ML_Conf
❤5🔥4🙏4
Новый трек — новые люди, которые собирают программу Practical ML Conf 🩵 Знакомим вас с программным комитетом, который формирует DS-программу конференции. Среди участников ПК — Борис Цейтлин, автор канала Борис опять, и Татьяна Гайнцева, автор канала DLStories. Подписывайтесь: 🔗 @Practical_ML_Conf
❤5👍4❤🔥3🔥1
Продолжаем знакомить вас с программным комитетом конференции 🐚 На очереди — трек NLP. Знакомим с экспертами, которые отбирают лучшие доклады о языковых моделях и их применении на практике. Среди участников ПК — Валентин Малых, автор канала Valuable AI, и Лаида Кушнарёва, автор канала Техножрица. Подписывайтесь: 🔗 @Practical_ML_Conf
❤5🔥4❤🔥2👏1🤩1😍1🙏1
Showing the 6 most recent of 6 posts we hold for @Practical_ML_Conf. 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.
Citation-graph rank — 297,368 of 1,151,006entries 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.
Named by 3 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.
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.
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 7 August 2026 — this entry's latest reading, not the date you are reading this.
“Practical ML Conf” (@Practical_ML_Conf), 182 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/Practical_ML_Conf.
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.