Telegram RegisterThe public register of Telegram
Telegram profile photo for Machine Learning | Нейронные сети, ИИ, Big Data

Channel

Machine Learning | Нейронные сети, ИИ, Big Data

@ML_secrets

On this record: Topic · Growth · Engagement · What this channel posts · Advertising · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry

7,365subscribers

-81 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001278052002
TypeChannel
Username@ML_secrets
DescriptionВсё о Machine Learning простым языком. Сотрудничество: @max_excel
CreatedBetween 1 April 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live9 November 2026
Measurements held22
Confirmed unchanged1 time, most recently 9 November 2026
On Telegramt.me/ML_secrets

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 12 September 2026 and assigned it the closest of 31 fixed categories, at 91% 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

7,3657,4467,405.57 August 2026 — 7,446 subscribers7 August 2026 — 7,446 subscribers14 August 2026 — 7,442 subscribers16 August 2026 — 7,443 subscribers20 August 2026 — 7,445 subscribers23 August 2026 — 7,439 subscribers27 August 2026 — 7,432 subscribers1 September 2026 — 7,430 subscribers5 September 2026 — 7,423 subscribers10 September 2026 — 7,410 subscribers18 September 2026 — 7,408 subscribers27 September 2026 — 7,398 subscribers11 October 2026 — 7,395 subscribers14 October 2026 — 7,393 subscribers17 October 2026 — 7,390 subscribers20 October 2026 — 7,385 subscribers24 October 2026 — 7,384 subscribers27 October 2026 — 7,382 subscribers30 October 2026 — 7,374 subscribers2 November 2026 — 7,372 subscribers5 November 2026 — 7,367 subscribers9 November 2026 — 7,365 subscribers7 August 20269 November 2026
22 measurements spanning 94 days, net -81. 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 7,353–7,458 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 22
Measured (UTC)SubscribersChange
9 Nov 2026, 07:577,365-2
5 Nov 2026, 14:187,367-5
2 Nov 2026, 12:407,372-2
30 Oct 2026, 03:347,374-8
27 Oct 2026, 00:357,382-2
24 Oct 2026, 07:057,384-1
20 Oct 2026, 21:277,385-5
17 Oct 2026, 16:297,390-3
14 Oct 2026, 18:087,393-2
11 Oct 2026, 12:007,395-3
27 Sept 2026, 00:597,398-10
18 Sept 2026, 01:187,408-2
10 Sept 2026, 04:187,410-13
5 Sept 2026, 04:577,423-7
1 Sept 2026, 10:187,430-2
27 Aug 2026, 00:047,432-7
23 Aug 2026, 20:367,439-6
20 Aug 2026, 08:027,445+2
16 Aug 2026, 22:237,443+1
14 Aug 2026, 00:437,442first reading

Engagement

53 posts held, back to 11 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 34 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
7.88%
avg views ÷ 7,365 subscribers
Avg views / post
580
10 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
10
of 53 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 9 November 2026
Posts held53 (11 June 2026 – 9 November 2026)
Views total5,801
Reactions total—
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 17:19 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
625
Videos
48
Links
731

Lifetime counters from Telegram’s own channel header, read 11 November 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.

Video runtime
6m 34s
Average length
6m 34s

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.

Advertising

Ad load
1.89%
1 of 53 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
494
over 1 measured post
Median views · rest
843
over 52 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2VtzqwQYm8S16 November 20266 November 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 53 most recent posts we hold, published 11 June 2026 to 9 November 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 10 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).

9 Nov 2026, 11:30 UTC336 viewsread 11 November 2026
Photo

🍤 Приделываем руки к ChatGPT: бот, который исполняет код в рантайме Как многие уже убедились, ИИ хорош, но есть некоторые типы задач, с которыми у него возникают трудности: 1. Он не может получать новые актуальные знания из сети. 2. Он не может выполнить какие‑либо действия. 3. У него сложности с алгоритмическими задачами (перевернуть строку, решить уравнение, произвести вычисления с применением численных методов).…

9 Nov 2026, 08:30 UTC341 viewsread 11 November 2026
Photo

Хочешь разбираться в 1С? Для тебя уже всё сделали. ⚙️ Канал 1С Hacks рассказывает обо всех возможностях, приёмах и лайфхаках по работе в 1С. Подписывайтесь и прокачивайте свои навыки: @secrets_1C

6 Nov 2026, 16:10 UTC468 viewsread 11 November 2026
Photo

🥬 ИИ может забрать у человека всю работу, но точно обещает оставить одну Поскольку ИИ угрожает захватить мир труда, по крайней мере одна довольно хорошая работа всегда будет востребована. Читайте, что бы узнать какая... Machine Learning

6 Nov 2026, 14:04 UTC494 viewsread 11 November 2026
Advertisementerid 2VtzqwQYm8SPhoto

Осенний Avito ML Cup: ранжирование ленты рекомендаций и призовой фонд 1,5 млн ₽ В этот раз задача про ранжирование, а призовой фонд вырос вдвое. Решать можно самостоятельно или в команде до четырёх человек. Какую задачу решаем. Для каждой рекомендательной ленты Авито уже отобраны кандидаты. Изучите историю пользователя и признаки объявлений, а потом расставьте кандидатов так, чтобы выше оказались те, с которыми чел…

2 Nov 2026, 11:25 UTC614 viewsread 11 November 2026
Photo

Как чат-бот с искусственным интеллектом может помочь блокчейн-разработчикам и финансовым аналитикам Разбираемся, что такое ChatGPT и какое влияние он может оказать на криптоиндустрию и digital-профессии. Machine Learning

29 Oct 2026, 11:25 UTC696 viewsread 11 November 2026
Video

5 лучших книг по Machine Learning и Data Science Искусственный интеллект, машинное обучение и нейронные сети стали неотъемлемой частью нашей повседневной жизни. Это уже не какое-то перспективное будущее, а вполне реальное настоящее. Спрос, как известно, рождает предложение, поэтому ресурсов и источников для изучения становится все больше и больше. В этом видео автор поделится своей подборкой 5 лучших книг по Data S…

25 Oct 2026, 12:15 UTC673 viewsread 11 November 2026
Photo

🏇 Выбираем инструмент MLOps Представляем вашему вниманию некоторые из самых популярных инструментов MLOps. Статья представляет собой краткий обзор основных функций, включая гайд о настройке и запуска пайплайна. Machine Learning

22 Oct 2026, 10:10 UTC723 viewsread 11 November 2026
Photo

♾ Можно ли доверять ответам на математические вопросы ChatGPT и другим языковым моделям? Исследования говорят, что ChatGPT имеет возможности в математике, которые ниже уровня среднего аспиранта. Это свидетельствует о том, что существуют некоторые ограничения у искусственного интеллекта в данной области. Machine Learning

19 Oct 2026, 11:25 UTC681 viewsread 11 November 2026
Photo

🙂 Автоматизация машинного обучения В этой статье автор рассматривает применение трех решений оптимизации рабочего процесса. Генератор признаков featuretools, подборщик гиперпараметров optuna и коробочное решение автоматического машинного обучения от H2O AutoML. Вы сравните работу новых инструментов против классических pandas и sklearn. Machine Learning

15 Oct 2026, 11:25 UTC775 viewsread 11 November 2026
Photo

Опенсорс-библиотеки для Python: 40+ вариантов, как упростить жизнь начинающего дата-сайентиста В этой обширной «шпаргалке» для начинающих AI/ML специалистов автор собрал опенсорсные библиотеки Python, сгруппированные по областям практического применения. Этот список с кратким описанием функций каждого инструмента будет полезен всем, кто постоянно работает с «Питоном» и ищет эффективные инструменты для решения возник…

11 Oct 2026, 10:05 UTC801 viewsread 11 November 2026
Photo

Плюсы и минусы ИИ чат-ботов. Решение всех проблем или грамотный маркетинг? В современную цифровую эпоху чат-боты на ИИ быстро становятся неотъемлемой частью онлайн-бизнеса. Их способность обеспечивать круглосуточное обслуживание клиентов, одновременно обрабатывать множество запросов клиентов и их общая эффективность в улучшении пользовательского пути сделали их все более популярными во многих отраслях, от электронно…

9 Oct 2026, 12:40 UTC796 viewsread 11 November 2026
Photo

👨‍👩‍👧‍👦 Объясните так, как будто мне 10 лет: простое описание популярного алгоритма кластеризации k-средних В статье объясним всем новичкам в мире алгоритмов машинного обучения принципы работы алгоритма K-means (k-средних), пользующегося большой популярностью при решении задач кластеризации. Постараемся избавиться от устрашающих математических нюансов и объяснить на уровне интуитивного понимания. Machine Learning

Showing the 12 most recent of 53 posts we hold for @ML_secrets. 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 recorded as deleted after publishing

We recorded 5 posts on @ML_secrets as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.

A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.

First seen missing
18 August 2026
Most recent seen missing
10 November 2026
Median time before seen missing
8 days
Seen missing in the last 30 days
2

Mentions

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.

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.

Базы данных | Access, SQL, Big Data
@databases_secrets · 30,000
Telegram ranks this channel #7 of 82 here — alongside 81 others — read 7 September 2026
Управление персоналом | hr, карьера, кадры
@secrets_hr · 21,770
Telegram ranks this channel #9 of 93 here — alongside 92 others — read 22 September 2026
Python Hacks
@python_secrets · 40,332
Telegram ranks this channel #9 of 82 here — alongside 81 others — read 30 August 2026
Секреты аналитики | Data Science, BI, Tableau
@analytics_secrets · 46,814
Telegram ranks this channel #10 of 85 here — alongside 84 others — read 27 August 2026
Финансовый анализ
@fin_analytics · 41,538
Telegram ranks this channel #18 of 87 here — alongside 86 others — read 29 August 2026
Excel Hacks | Бухгалтерия и Аналитика
@hacks_excel · 283,052
Telegram ranks this channel #18 of 85 here — alongside 84 others — read 10 August 2026
1С Hacks | Бухгалтерия и Учёт
@secrets_1C · 46,459
Telegram ranks this channel #30 of 79 here — alongside 78 others — read 27 August 2026
Системный и Бизнес-анализ
@ba_sa_analytics · 52,458
Telegram ranks this channel #31 of 90 here — alongside 89 others — read 24 August 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,923
Telegram ranks this channel #33 of 93 here — alongside 92 others — read 25 August 2026
Data Science | Machinelearning [ru]
@devsp · 19,651
Telegram ranks this channel #37 of 91 here — alongside 90 others — read 30 September 2026
Математика | Геометрия
@algebra_shpargalki · 23,756
Telegram ranks this channel #40 of 86 here — alongside 85 others — read 17 September 2026
Python Learning
@Python_per_month · 27,870
Telegram ranks this channel #41 of 86 here — alongside 85 others — read 9 September 2026
Однажды в трендах
@trendo · 66,417
Telegram ranks this channel #48 of 90 here — alongside 89 others — read 20 August 2026
Полка Разработчика
@developer_shelf · 26,715
Telegram ranks this channel #50 of 63 here — alongside 62 others — read 11 September 2026
Senior Python Developer
@seniorpy · 39,134
Telegram ranks this channel #50 of 92 here — alongside 91 others — read 30 August 2026
ЭКСЕЛЬХАК
@excelhackru · 74,003
Telegram ranks this channel #55 of 87 here — alongside 86 others — read 19 August 2026
Data Science
@datascienceiot · 42,496
Telegram ranks this channel #56 of 76 here — alongside 75 others — read 29 August 2026
Python и 1000 уязвимостей
@osint_pythons · 36,463
Telegram ranks this channel #59 of 84 here — alongside 83 others — read 1 September 2026
Python обучающий
@pythonist24 · 55,221
Telegram ranks this channel #59 of 88 here — alongside 87 others — read 23 August 2026
DataFlair
@dataflair · 18,577
Telegram ranks this channel #72 of 83 here — alongside 82 others — read 4 October 2026

This channel appears in 20 seed channels' Telegram-generated recommendation lists in total. 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 9 November 2026 — this entry's latest reading, not the date you are reading this.

“Machine Learning | Нейронные сети, ИИ, Big Data” (@ML_secrets), 7,365 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/ML_secrets.

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.