Channel
@kaggle_fucker
On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry
1,242subscribers
-2 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001343511450 |
|---|---|
| Type | Channel |
| Username | @kaggle_fucker |
| Created | Between 1 April 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/kaggle_fucker |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 18:05 | 1,242 | -2 |
| 7 Aug 2026, 23:02 | 1,244 | no change |
| 7 Aug 2026, 12:27 | 1,244 | first reading |
20 posts held, back to 7 June 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 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 8 December 2025. An engagement rate over an empty window would be a number about nothing.
Measured directly from 1 video 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.
417 reactions across 20 posts, in 15 distinct kinds. The most used accounts for 32.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 135 | 32.4% | |
| 👍 | 87 | 20.9% | |
| 🔥 | 76 | 18.2% | |
| 😁 | 76 | 18.2% | |
| 🤡 | 12 | 2.88% | |
| 💩 | 9 | 2.16% | |
| 👎 | 7 | 1.68% | |
| 😱 | 3 | 0.719% | |
| 🤨 | 3 | 0.719% | |
| 🫡 | 3 | 0.719% | |
| 🤔 | 2 | 0.48% | |
| ⚡ | 1 | 0.24% | |
| 🌚 | 1 | 0.24% | |
| 🗿 | 1 | 0.24% | |
| 🤗 | 1 | 0.24% |
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 417reactions 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 7 June 2024 to 8 December 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 @kaggle_fucker. 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 20 most recent posts we hold for this entry, published 7 June 2024 to 8 December 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.
Наконец завершили проведение соревнования AIJ по памяти GigaMemory. Это был мой первый очень нервный, но очень интересный опыт проведения такого масштабного контеста. Огромное спасибо всем организаторам и участникам! Разобрали топовые решения в хабр-статье: https://habr.com/ru/companies/sberbank/articles/974310/
❤12👍4
Signed Mark Baushenko
Всем привет! 👋 Сегодня буду стоять на постерной сессии на AIJ. Можете подходить и я вам расскажу как мы делали память в GigaChat.
🔥15👍7
Signed Mark Baushenko
Устал от Литкода? Попробуй другой подход. Все знают этот рутинный путь к найму в крупные IT-компании: открываешь leetcode.com или neetcode.io и решаешь задачи до тех пор, пока if x != y: не начинает сниться. Процесс необходимый, но откровенно надоедает. Нашел в Steam игру, которая прокачает твои алгоритмические скиллы под видом увлекательной автоматизации. Называется The Farmer Was Replaced. 🎯В чем суть: Фермер исч…
❤17👍3
Signed Mark Baushenko
Вспомнить все: трек памяти для LLM на AIJ contest 2025. Приоткрыли завесу тайны, что за соревнование, дали пару советов и кое-что пошерили для вас. P.S. И как вовремя qwen.chat.ai выпустили свой вариант ассистента с памятью. Хороший обзор у коллеги по цеху. Лайк на Хабре, участие в соревке и ваши мысли, приветствуются ;) https://habr.com/ru/companies/sberbank/articles/957292/
👍4❤1
Signed Mark Baushenko
🚀 VK запустила RecSys Challenge 2025, где можно подраться с настоящей промышленной задачей и крупным призовым фондом. 🎯 Что за соревнование? Задача здесь зеркальная классической: нужно не подбирать контент под пользователя, а находить целевую аудиторию для нового клипа, который еще никто не видел («холодный старт»). Формат решения: для каждого нового видео нужно предсказать упорядоченный список из 100 пользователей…
👍4👎1🔥1
Signed Mark Baushenko
Сегодня буду на Practical ML Conf. Вы тоже заранее смотрите программу и составляете себе расписание на конфу?) Кароч выделил для себя интересные доклады, тут в основном все что связано с LLM и RecSys. LLM потому что напрямую связано с моей работой, а RecSys часто встречается в соревнованиях, поэтому надо быть в курсе. - 14:20-14:55, зал Данные Память и online-RL: опыт YandexGPT 5.1 - 14:55-15:35, зал Данные Создан…
❤9👍1
Signed Mark Baushenko
Пост помощи ❤️ Есть уже собранный компьютер. Задача из него сделать 2 компьютера докупив комплектующие и потом настроить все. Кто за это шарит в лс напишите плиз🙏🏼
👍6
Signed Mark Baushenko
Всем привет 👋 , чет я подзабросил группу, но пора возобновлять ее вести. Во время моего отсутствия я занимался новым проектом связанным с долгосрочной глобальной памятью в LLM. Было перечитано десятки статей, были построены десятки MVP, что-то заработало, а что-то улетело в ящик и возможно навсегда. Пока без подробностей, потому что проект NDA, но можно посмотреть выступление (тайм-код 1:33:00, хз как в ВК видео ссы…
❤28🔥6👍3🤔1
Signed Mark Baushenko
Привет всем!👋 Ловите подборку мероприятий, на которые можно сходить в ближайшее время: В 🏦 пройдет Turbo ML Conf Достаточно интересное мероприятие, включающее большое количество докладов в разных областях DS. Выступления будут поделены на 5 секций: NLP, Research & RnD, LLM Applications & Copilots, RecSys, CV & Speech 📍Локация: Москва, Раменский бул., 1, кластер Ломоносов 📆 Время: 19 июля 👉 Регистрация по ссылке 👨…
🔥8👍4❤1🫡1
Signed Mark Baushenko
Искусственный интеллект повсюду…
😁15🤡8😱3❤2
Signed Mark Baushenko
Ох уж этот Augmentex ))
🔥6
Signed Mark Baushenko
Да уж, вот вам и текстовые аугментации #ShitPost
😁20❤2
Signed Mark Baushenko
Showing the 12 most recent of 20 posts we hold for @kaggle_fucker. 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 — 570,334 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.
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.
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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“MarksRemarks” (@kaggle_fucker), 1,242 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/kaggle_fucker.
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.