Telegram RegisterThe public register of Telegram
Telegram profile photo for Yandex for ML

Channel

Yandex for ML

@yandexforml

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

19,130subscribers

+487 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001433806174
TypeChannel
Username@yandexforml
Description💙Канал для ML-сообщества от Яндекса и место встречи специалистов в сфере анализа данных. Чат→ https://t.me/+XR1fd2QNnaIxNTUy Вопросы: @Ekaterina_Lyagina Все каналы по стекам: https://t.me/addlist/Hrq31w2p1vUyOGZi
CreatedBetween 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live6 November 2026
Measurements held56
Confirmed unchanged1 time, most recently 6 November 2026
On Telegramt.me/yandexforml

Topic

Technology — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 88% 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 the other topics.

Growth

18,64319,13018,886.56 August 2026 — 18,643 subscribers6 August 2026 — 18,645 subscribers9 August 2026 — 18,650 subscribers10 August 2026 — 18,648 subscribers11 August 2026 — 18,659 subscribers11 August 2026 — 18,665 subscribers13 August 2026 — 18,675 subscribers14 August 2026 — 18,685 subscribers15 August 2026 — 18,697 subscribers16 August 2026 — 18,705 subscribers17 August 2026 — 18,714 subscribers19 August 2026 — 18,721 subscribers19 August 2026 — 18,764 subscribers20 August 2026 — 18,755 subscribers22 August 2026 — 18,759 subscribers24 August 2026 — 18,760 subscribers25 August 2026 — 18,761 subscribers26 August 2026 — 18,764 subscribers26 August 2026 — 18,772 subscribers27 August 2026 — 18,781 subscribers28 August 2026 — 18,784 subscribers29 August 2026 — 18,783 subscribers30 August 2026 — 18,784 subscribers1 September 2026 — 18,783 subscribers1 September 2026 — 18,797 subscribers2 September 2026 — 18,800 subscribers4 September 2026 — 18,808 subscribers7 September 2026 — 18,820 subscribers10 September 2026 — 18,829 subscribers12 September 2026 — 18,837 subscribers13 September 2026 — 18,850 subscribers15 September 2026 — 18,844 subscribers17 September 2026 — 18,854 subscribers28 September 2026 — 18,921 subscribers5 October 2026 — 18,948 subscribers9 October 2026 — 18,992 subscribers13 October 2026 — 19,033 subscribers14 October 2026 — 19,038 subscribers15 October 2026 — 19,046 subscribers16 October 2026 — 19,053 subscribers17 October 2026 — 19,057 subscribers20 October 2026 — 19,066 subscribers20 October 2026 — 19,073 subscribers22 October 2026 — 19,087 subscribers25 October 2026 — 19,091 subscribers26 October 2026 — 19,099 subscribers27 October 2026 — 19,105 subscribers27 October 2026 — 19,112 subscribers29 October 2026 — 19,117 subscribers30 October 2026 — 19,119 subscribers31 October 2026 — 19,124 subscribers1 November 2026 — 19,123 subscribers3 November 2026 — 19,124 subscribers4 November 2026 — 19,125 subscribers5 November 2026 — 19,129 subscribers6 November 2026 — 19,130 subscribers6 August 20266 November 2026
56 measurements spanning 92 days, net +487. 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 18,570–19,203 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 56
Measured (UTC)SubscribersChange
6 Nov 2026, 03:4119,130+1
5 Nov 2026, 06:1019,129+4
4 Nov 2026, 07:5119,125+1
3 Nov 2026, 10:3819,124+1
1 Nov 2026, 05:2719,123-1
31 Oct 2026, 05:4819,124+5
30 Oct 2026, 04:4519,119+2
29 Oct 2026, 03:3519,117+5
27 Oct 2026, 23:5019,112+7
27 Oct 2026, 01:1019,105+6
26 Oct 2026, 01:4719,099+8
25 Oct 2026, 03:4619,091+4
22 Oct 2026, 01:1619,087+14
20 Oct 2026, 22:1919,073+7
20 Oct 2026, 00:2819,066+9
17 Oct 2026, 21:1719,057+4
16 Oct 2026, 21:5819,053+7
15 Oct 2026, 19:5719,046+8
14 Oct 2026, 20:3919,038+5
13 Oct 2026, 12:1619,033first reading

Engagement

30 posts held, back to 30 July 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 63 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
13.3%
avg views ÷ 19,130 subscribers
Avg views / post
2,550
2 posts measured
Reaction rate
1.04%
reactions ÷ views · ER floor
Posts in window
2
of 30 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 5 November 2026
Posts held30 (30 July 2026 – 5 November 2026)
Views total5,100
Reactions total53
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Nov 2026, 15:28 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
≈1,320
Videos
≈85
Links
≈535

Lifetime counters from Telegram’s own channel header, read 6 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
2m 04s
Average length
41s

Measured directly from 3 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.

Reaction mix

841 reactions across 29 posts, in 16 distinct kinds. The most used accounts for 44.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤37644.7%
🔥20424.3%
👍748.80%
❤‍🔥576.78%
👏475.59%
👎232.73%
🦄141.66%
😱111.31%
👀91.07%
🎉80.951%
😁60.713%
🥰40.476%
😍30.357%
✍20.238%
😢20.238%
🤩10.119%

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 29 of the 30 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 841 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 30 most recent posts we hold, published 30 July 2026 to 5 November 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.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 2 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

5 Nov 2026, 12:02 UTC≈1,940 views15 reactionsread 6 November 2026
Photo

🧿 RuntimeNodes: как ML-разработчики в Яндексе начали писать рантайм сами Привет, это Ильнур Хузиев, руководитель службы генеративного ответа Алисы AI. Я работаю в команде, которая переносит ML-эксперименты для генеративных ответов Алисы AI в Поиске из офлайна в продакшен. Офлайн‑прототипы у нас обычно строятся поверх MapReduce‑хранилища. В Яндексе для этого используется YTsaurus. Пайплайны, как правило, описываются…

❤10👍2🔥2😁1

2 Nov 2026, 12:07 UTC≈3,160 views38 reactionsread 6 November 2026
Photo

📺 Practical ML Conf: записи всех докладов Смотрите выступления про лучшие ML-практики и вдохновляйтесь. Кто знает, куда вас заведут эксперименты: может, вы станете одним из спикеров конференции 2027 года. Записи докладов мы разделили по залам: ⚪️ «Данные» на ютубе и в VK Видео ⚪️ «Код» на ютубе и в VK Видео ⚪️ «Сеть» на ютубе и в VK Видео ⚪️ «Серверная» на ютубе и в VK Видео Keynotes выделили отдельно: ⚪️ Доклад…

❤27🔥8😍3

7 Oct 2026, 11:30 UTC≈5,420 views21 reactionsread 6 November 2026
Photo

🪧 Строим логистику пути в ML Привет всем, меня зовут Фархад Сабилов, я руковожу группой ML игровых и коммуникационных механик в Яндекс Плюс AdTech. Ещё во время учёбы в университете я устроился на первую фултайм-работу: начал помощником логиста и за три года стал руководителем сразу в трёх компаниях холдинга. В какой-то момент мне захотелось сменить карьерный трек. Несколько лет я искал себя, попробовал открыть сво…

❤11🔥5👍3👀2

5 Oct 2026, 12:31 UTC≈4,600 views17 reactionsread 6 November 2026
Photo

🔎 Открываем претрейн Alice AI Search Быстрый ответ Алисы AI — это самый массовый генеративный продукт Яндекса и первая точка контакта с Алисой для пользователей Поиска. Даже в час пиковой нагрузки он должен появляться за секунды. Поэтому мы, команда Alice AI Search, решили адаптировать весь пайплайн: от собственного претрейна с кастомной архитектурой до online RL на поведенческих сигналах аудитории. Alice AI Search…

❤12👏4✍1

3 Oct 2026, 10:01 UTC≈4,770 views29 reactionsread 6 November 2026
Photo

📕 Выкатываем AliceAI-Foundation-80B-A3B-Base в опенсорс, занимаемся ML-разработкой без написания кода и (внезапно) пишем рантайм. Об этом и не только — в новом ML-дайджесте 🚕 Куда сходить 🔴 6 октября — Архитектурный клуб Яндекс 360 онлайн. Открытое сообщество для архитекторов и инженеров, которые строят высоконагруженные системы. На этот раз разберём архитектуру AI-агента над корпоративными данными: от оркестратора…

❤15❤‍🔥5👍5🔥2😁1😢1

2 Oct 2026, 11:04 UTC≈4,380 views15 reactionsread 6 November 2026
Photo

💻 Как заниматься ML-разработкой без написания кода 👋 Всем привет, это Руслан Кулиев, разработчик в службе клиентского ML в Яндекс Лавке. Последние полгода я развивал наши трансформерные технологии на базе Argus и локальную среду для DL-экспериментов. За это время из более чем 100 тысяч строк финального кода я не написал ни одной: разработка и эксперименты были целиком AI-first. 👷 В карточках я поделился некоторыми …

❤10🔥3👀1👍1

29 Sept 2026, 11:45 UTC≈4,980 views73 reactionsread 6 November 2026
Video

🧑‍🏫 Data Dojo: встреча ML-сообщества в Москве 🔳 28 октября мы соберёмся на Data Dojo — митапе для тех, кому интересно машинное обучение. Здесь вас ждут прикладные доклады от экспертов, нетворкинг, мастер-классы, мерч и многое другое. На ивенте начинающие ML-специалисты смогут попасть в тусовку, познакомиться с трендами индустрии и получить карьерную консультацию. А опытные инженеры — найти единомышленников и завест…

❤31🔥21👍17❤‍🔥3🦄1

28 Sept 2026, 13:03 UTC≈4,410 views33 reactionsread 5 November 2026
Video

🎉 Practical ML Conf 2026 завершилась, но впечатлений хватит на весь год 🔳 Последние новости с конференции: спикеры выступили, Yandex ML Prize вручили, подарки раздали, дискуссии провели. Получилось очень здорово: участники знакомились с сервисами Яндекса, пробовали новое, нетворкали и делились инсайтами. Спасибо всем, кто был с нами: конфу в Москве посетили 870 участников, а онлайн-трансляция собрала около 2000 зри…

❤‍🔥15❤9🎉7👍1🔥1

2 Sept 2026, 09:02 UTC≈1,680 views37 reactionsread 3 September 2026
Photo

🧿 Одна модель вместо всего рекомендательного стека Яндекс Музыки Привет, это Николай Савушкин, руководитель службы рекомендательных технологий Яндекс R&D. В августе мы опубликовали Sona Technical Report — результат года нашей работы над новой генеративной end-to-end-моделью рекомендаций. Раньше все рекомендации в Музыке проходили через многоступенчатый каскад: отбором занимались больше 15 кандидатогенераторов, а за…

🔥19❤11❤‍🔥5✍1🦄1

1 Sept 2026, 10:10 UTC≈2,400 views56 reactionsread 3 September 2026
Photo

🎓 Как преподаватель математики стала руководителем ML-направления в ШАДе Привет, это Валя Бронер. Я 11 лет преподавала студентам математику в Томском государственном университете, а затем перешла в бигтех. Последние три года я руковожу ML-направлением в ШАДе Яндекса и создаю курсы по машинному обучению. Сегодня я расскажу, что мне нравится в преподавании, почему решила уйти из вуза в ШАД и как ML-разработчики помог…

❤23🔥18❤‍🔥7😱6👎1😢1

28 Aug 2026, 12:00 UTC≈3,460 views24 reactionsread 3 September 2026
Photo

📎 Найти баланс между ресёрчем и инженерией Всем привет, это Никита Корягин, ML-инженер в команде алайнмента Alice AI. До того как устроиться в Яндекс, я довольно много занимался ресёрчем: экспериментировал с моделями, писал статьи, публиковался на конференциях. Такой формат мне всё ещё очень близок, но в какой-то момент я захотел получать больше практической отдачи от работы: увидеть, как идея доезжает до реальной м…

❤9🔥9👍5❤‍🔥1

27 Aug 2026, 12:02 UTC≈3,300 views27 reactionsread 3 September 2026
Photo

🍫 Как мы читаем даты изготовления с фотографий На связи Роман Шинкаренко, я разработчик в службе AI-сервисов Лавки. В новом посте рубрики «Обучено Яндекс Лавкой» расскажу, как мы обрабатываем жалобы пользователей на качество товара в доставке. В процессе обсудим, как нам в этом помогает AI-агент и как мы научили его отвечать честно. 🅿️ Поддержка заводит тикет с тегом и фотографиями Сотрудник техподдержки открывает…

❤9👍7🔥6👎4❤‍🔥1

Showing the 12 most recent of 30 posts we hold for @yandexforml. 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.

Posts edited after publishing

@yandexforml edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
2 September 2026
Most recent edit
2 September 2026

Forward network

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 7 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.

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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

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#54
MLinside - школа ML
@ml_inside · 4,080
#55
Купер.тех
@tech_kuper · 8,089
#56
AbstractDL
@abstractDL · 18,843
#57
WildRecSys
@wildrecsys · 1,870
#58
AI для Всех
@nn_for_science · 15,475
#59
DziS Science | Data Science
@dzis_science · 2,193
#60
🦒∵ girafe.ai
@girafe_ai · 3,751
#61
Инжиниринг Данных
@rockyourdata · 23,686
#62
Derp Learning
@derplearning · 14,000
#63
Стать специалистом по машинному обучению
@toBeAnMLspecialist · 10,870
#64
Рекомендательная [RecSys Channel]
@RecSysChannel · 3,242
#65
Neural Shit
@NeuralShit · 54,660
#66
karpov.courses
@KarpovCourses · 27,307
#67
RnD ML Team
@rndml_team · 4,226
#68
gonzo-обзоры ML статей
@gonzo_ML · 24,681
#69
Машинное обучение RU
@machinelearning_ru · 18,350
#70
ODS #jobs
@odsjobs · 14,549
#71
еба́ные идеи для резерча
@ebaresearch · 5,380
#72
New Yorko Times
@new_yorko_times · 10,702
#73
Kali Novskaya
@rybolos_channel · 19,138
#74
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 47,060
#75
Старший Авгур
@senior_augur · 8,357
#76
Нескучный Data Science Jobs
@not_boring_ds_jobs · 9,407
#77
Dev & ML Connectable Jobs
@dev_connectablejobs · 29,046
#78
ФКН: Вакансии
@vacancy_cs · 18,389
#79
grokaem себя
@grokaem_seby · 2,756
#80
Take Friends to Luna Park
@hrlunapark · 20,975
#81
Т-Образование
@tbank_education · 113,581
#82
ФКН НИУ ВШЭ
@fcs_hse · 14,707
#83
Data Science Jobs
@datasciencejobs · 22,544
#84
Заметки Computer Vision инженера
@CVML_team · 6,118
#85
Data jobs — вакансии по data science, анализу данных, аналитике, искусственному интеллекту
@datajob · 15,107
#86
Сергей Марков: машинное обучение, искусство и шитпостинг
@oulenspiegel_channel · 12,324
#87
Нейронки и вино
@neural_wine · 1,935
#88
Анализ данных (Data analysis)
@data_analysis_ml · 51,929
#89
Data Science Jobs
@datascienceml_jobs · 21,625
#90
rizzearch
@rizzearch · 1,006
#91
Зарплатник Аналитика
@zarplatnik_analytics · 11,699
#92
̶с̶а̶м̶̶о̶изолента мёбиуса
@izolenta_mebiusa · 2,775
#93
Записки Ппилифа
@ppilif_chanel · 4,492
#94
Phystech.Career
@phystechcareerchannel · 7,610
#95
addmeto
@addmeto · 71,985
#96

Read from Telegram’s recommendation API, most recently 4 October 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

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.

Yandex for Developers
@Yandex4Developers · 28,654
Telegram ranks this channel #5 of 94 here — alongside 93 others — read 9 September 2026
Яндекс Образование
@Education_Yandex · 38,058
Telegram ranks this channel #8 of 96 here — alongside 95 others — read 31 August 2026
8БИТ. Журнал Яндекс Образования
@journal_yandex_education · 18,803
Telegram ranks this channel #9 of 97 here — alongside 96 others — read 4 October 2026
Young&&Yandex
@Young_and_Yandex · 112,984
Telegram ranks this channel #9 of 92 here — alongside 91 others — read 14 August 2026
Яндекс нанимает | Вакансии для разработчиков
@ya_jobs · 33,134
Telegram ranks this channel #10 of 96 here — alongside 95 others — read 5 September 2026
Machinelearning
@ai_machinelearning_big_data · 276,200
Telegram ranks this channel #10 of 95 here — alongside 94 others — read 10 August 2026
Data Science | Machinelearning [ru]
@devsp · 19,680
Telegram ranks this channel #12 of 91 here — alongside 90 others — read 30 September 2026
Machine learning Interview
@machinelearning_interview · 30,581
Telegram ranks this channel #13 of 98 here — alongside 97 others — read 7 September 2026
Stepik – онлайн-курсы
@stepik_courses · 28,924
Telegram ranks this channel #14 of 93 here — alongside 92 others — read 16 September 2026
Data Secrets
@data_secrets · 95,989
Telegram ranks this channel #19 of 98 here — alongside 97 others — read 17 August 2026
karpov.courses
@KarpovCourses · 27,307
Telegram ranks this channel #20 of 96 here — alongside 95 others — read 10 September 2026
Время Валеры
@cryptovalerii · 32,021
Telegram ranks this channel #21 of 94 here — alongside 93 others — read 6 September 2026
Код Желтый
@kod_zheltyi · 33,548
Telegram ranks this channel #21 of 96 here — alongside 95 others — read 4 September 2026
XOR
@xor_journal · 198,734
Telegram ranks this channel #22 of 93 here — alongside 92 others — read 12 August 2026
gonzo-обзоры ML статей
@gonzo_ML · 24,681
Telegram ranks this channel #23 of 93 here — alongside 92 others — read 16 September 2026
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 47,060
Telegram ranks this channel #27 of 90 here — alongside 89 others — read 28 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 70,223
Telegram ranks this channel #27 of 94 here — alongside 93 others — read 20 August 2026
Data Science
@datascienceiot · 42,540
Telegram ranks this channel #28 of 76 here — alongside 75 others — read 29 August 2026
эйай ньюз
@ai_newz · 98,218
Telegram ranks this channel #30 of 94 here — alongside 93 others — read 16 August 2026
Sber AI
@SberAIScience · 26,546
Telegram ranks this channel #34 of 95 here — alongside 94 others — read 10 September 2026
LLM под капотом
@llm_under_hood · 30,121
Telegram ranks this channel #34 of 96 here — alongside 95 others — read 9 September 2026
Сиолошная
@seeallochnaya · 81,039
Telegram ranks this channel #35 of 97 here — alongside 96 others — read 19 August 2026
VK Team
@vkjobs · 25,867
Telegram ranks this channel #36 of 97 here — alongside 96 others — read 13 September 2026
Ozon Tech
@ozon_tech · 30,150
Telegram ranks this channel #36 of 98 here — alongside 97 others — read 8 September 2026

This channel appears in 39 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 6 November 2026 — this entry's latest reading, not the date you are reading this.

“Yandex for ML” (@yandexforml), 19,130 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/yandexforml.

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.