Channel
@rcppe
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
281subscribers
-3 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002223086568 |
|---|---|
| Type | Channel |
| Username | @rcppe |
| Created | Between 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 16 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 16 August 2026 |
| On Telegram | t.me/rcppe |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Aug 2026, 16:18 | 281 | -3 |
| 8 Aug 2026, 08:30 | 284 | no change |
| 7 Aug 2026, 23:12 | 284 | first reading |
20 posts held, back to 20 January 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 20 posts for this entry, the most recent from 30 April 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
213 reactions across 20 posts, in 8 distinct kinds. The most used accounts for 39.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤🔥 | 84 | 39.4% | |
| 🔥 | 79 | 37.1% | |
| ❤ | 21 | 9.86% | |
| 🤣 | 10 | 4.69% | |
| 👍 | 9 | 4.23% | |
| 😁 | 5 | 2.35% | |
| 👏 | 3 | 1.41% | |
| 🥰 | 2 | 0.939% |
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 20 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 213reactions 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 20 January 2026 to 30 April 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.
Что такое SGD? Stochastic Gradient Descent — это стохастический градиентный спуск. Он обновляет параметры не по всему датасету, а по одному примеру или мини-батчу. Объясняем за 13 секунд👇 👁 Youtube Shorts: https://youtube.com/shorts/pQ1pgS4uAcA 👁 VK Клипы: https://vk.com/clip-123163949_456239331 👁 Instagram Reels: https://www.instagram.com/p/DXw0xPap2OZ/ 👁 Rutube Shorts: https://rutube.ru/shorts/d4c18081acfcb14bca3e…
🔥9❤🔥2❤1
Что такое Inner Product / Dot Product? Скалярное произведение — это произведение двух векторов: мы умножаем соответствующие элементы и складываем результаты. Объясняем за 15 секунд👇 👁 Youtube Shorts: https://youtube.com/shorts/pAuZ9Ldsvkc 👁 VK Клипы: https://vk.com/clip-214877772_456239329 👁 Instagram Reels: https://www.instagram.com/p/DXh9MoIJ4GW/ 👁 Rutube Shorts: https://rutube.ru/shorts/430dd847ad6107323508641303…
❤🔥5🔥2🥰1
Что такое Gradient Descent? Градиентный спуск (Gradient descent) — это метод оптимизации, который шаг за шагом уменьшает ошибку модели, двигаясь в сторону наибольшего убывания функции потерь. Объясняем за 10 секунд👇 👁 Youtube Shorts: https://youtube.com/shorts/KH5h4BBdL1A 👁 VK Клипы: https://vk.com/clip-214877772_456239327 👁 Instagram Reels: https://www.instagram.com/p/DXZ4J9WJSYe/ 👁 Rutube Shorts: https://rutube.ru…
❤🔥5🔥3🥰1
Что такое VAE? Variational autoencoder (VAE) — это генеративный автоэнкодер, который не просто сжимает данные, а учит их вероятностное скрытое представление, чтобы потом генерировать новые похожие примеры. Объясняем за 16 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239322 👁 Youtube Shorts: https://youtube.com/shorts/Poac7gsX0kc 👁 Instagram Reels: https://www.instagram.com/p/DXWjJQrJn7W/ 👁 Rutube Shorts: htt…
🔥7❤🔥1
Что такое PCA? Метод главных компонент (Principal Component Analysis) — это алгоритм машинного обучения без учителя, используемый для снижения размерности данных при сохранении максимального количества информации (дисперсии, т.е. разброса). Объясняем за 20 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239320 👁 Youtube Shorts: https://youtube.com/shorts/JBcEzPLi6hk 👁 Instagram Reels: https://www.instagram.com/…
🔥7❤🔥3
Что такое Federated Learning? Федеративное обучение — это способ обучать модель на данных, которые не покидают устройства: вместо самих данных отправляются только обновления модели, которые потом объединяются на центральном сервере. Объясняем за 15 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239317 👁 Youtube Shorts: https://youtube.com/shorts/fWXUYvlkEtE 👁 Instagram Reels: https://www.instagram.com/p/DXRZAC…
❤🔥5🔥4
Что такое Walk-Forward Optimization? Walk-forward оптимизация — это способ проверять и подбирать параметры модели на временных рядах по шагам, чтобы избегать переобучения. Объясняем за 12 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239314 👁 Youtube Shorts: https://youtube.com/shorts/o6BSMpk3sQ0 👁 Instagram Reels: https://www.instagram.com/p/DXPNCPcJen-/ 👁 Rutube Shorts: https://rutube.ru/shorts/5352738a2824…
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Что такое Overfitting/Underfitting? Переобучение — это когда модель слишком хорошо запоминает обучающие данные, включая шум и случайные детали, и поэтому хуже работает на новых данных. Недообучение — это когда модель слишком простая и не улавливает закономерности в данных, поэтому плохо работает и на обучающих, и на новых данных. Объясняем за 15 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239310 👁 Youtube S…
❤🔥4🔥3
Что такое Conformal prediction? Конформное прогнозирование — это метод оценки неопределённости, который по данным калибровки строит множество допустимых ответов или интервал, так что истинное значение покрывается с заданной вероятностью, например 95%. Объясняем за 19 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239307 👁 Youtube Shorts: https://youtube.com/shorts/wPN7pvU_nRc 👁 Instagram Reels: https://www.ins…
🔥6❤🔥3
Сравнение интерактивных визуализаций по математике, физике и инженерии в ChatGPT и Gemini. Напишите в комментариях, где вам больше нравится. @rcppe
❤6🔥3👍2
Что такое Softmax? Softmax — это функция активации, которая применяется ко всему слою, а не к отдельному нейрону. Объясняем за 19 секунд👇 👁 VK Клипы: https://vk.com/clip-214877772_456239304 👁 Youtube Shorts: https://youtube.com/shorts/4IsdCtktrG0 👁 Instagram Reels: https://www.instagram.com/p/DXEWwoep1Jt/ 👁 Rutube Shorts: https://rutube.ru/shorts/5c17f3984b60ce017ea99fad3717318a/ #машинноеобучение #maths #нейросети…
❤🔥5🔥3
Пост от ректора АНО ДО «ВЦППИ» @a_shaikhutdinov Андрей Карпатый запустил аналог соцсетей X и Threads, но с запретом на нейрослоп. В KarpathyTalk запрещено подключать ИИ-агентов для написания постов. На любой сгенерированный текст можно пожаловаться, и разместившего его пользователя заблокируют. Ленту уже заполнили русскоязычные посты - соцсеть «захватили» русские программисты (зарегистрироваться можно только через Gi…
❤🔥6❤1
Showing the 12 most recent of 20 posts we hold for @rcppe. 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 — 143,205 of 1,548,671entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
Named by 1 registered channel — 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 16 August 2026 — this entry's latest reading, not the date you are reading this.
“АНО ДО «ВЦППИ»” (@rcppe), 281 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/rcppe.
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.