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Channel

Анализ данных (Data analysis)

@data_analysis_ml

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Advertising · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry

50,530subscribers

+141 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001684146975
TypeChannel
Username@data_analysis_ml
Created28 May 2022measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live22 August 2026
Measurements held16
Confirmed unchanged1 time, most recently 22 August 2026
On Telegramt.me/data_analysis_ml

Topic

Technology — a classification, not a measurement. 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 why it has no browse page of its own yet.

Growth

50,35750,53050,443.56 August 2026 — 50,389 subscribers6 August 2026 — 50,390 subscribers8 August 2026 — 50,389 subscribers9 August 2026 — 50,383 subscribers10 August 2026 — 50,384 subscribers11 August 2026 — 50,381 subscribers12 August 2026 — 50,376 subscribers13 August 2026 — 50,363 subscribers14 August 2026 — 50,357 subscribers15 August 2026 — 50,390 subscribers17 August 2026 — 50,398 subscribers18 August 2026 — 50,400 subscribers19 August 2026 — 50,442 subscribers20 August 2026 — 50,463 subscribers21 August 2026 — 50,487 subscribers22 August 2026 — 50,530 subscribers6 August 202622 August 2026
16 measurements spanning 17 days, net +141. 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 50,331–50,556 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
22 Aug 2026, 22:5450,530+43
21 Aug 2026, 15:4450,487+24
20 Aug 2026, 14:2250,463+21
19 Aug 2026, 12:0850,442+42
18 Aug 2026, 13:1350,400+2
17 Aug 2026, 09:4450,398+8
15 Aug 2026, 18:5250,390+33
14 Aug 2026, 05:3850,357-6
13 Aug 2026, 00:1450,363-13
12 Aug 2026, 00:2250,376-5
11 Aug 2026, 01:1750,381-3
10 Aug 2026, 03:4050,384+1
9 Aug 2026, 02:0150,383-6
8 Aug 2026, 01:1150,389-1
6 Aug 2026, 23:0050,390+1
6 Aug 2026, 01:5050,389first reading

Engagement

83 posts held, back to 31 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 38 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
10.2%
avg views ÷ 50,530 subscribers
Avg views / post
5,180
83 posts measured
Reaction rate
0.541%
reactions ÷ views · ER floor
Posts in window
83
of 83 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 22 August 2026
Posts held83 (31 July 202622 August 2026)
Views total429,760
Reactions total2,327
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken22 Aug 2026, 14:12 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

Video runtime
13m 05s
Average length
1m 11s

Measured directly from 11 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

2,218 reactions across 81 posts, in 26 distinct kinds. The most used accounts for 27.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍61627.8%
61227.6%
🔥45120.3%
🤣23210.5%
😁1275.73%
🥰261.17%
🥱220.992%
🥴190.857%
🤔170.766%
👏140.631%
😢130.586%
❤‍🔥100.451%
🤯100.451%
💯90.406%
60.271%
🤨60.271%
🍌40.18%
🎉40.18%
💔40.18%
🕊40.18%
6 further kinds120.541%

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 83 of the 83 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 2,327reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 83 most recent posts we hold, published 31 July 2026 to 22 August 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.

Telegram Stars

Stars received
2
across the posts below
Posts paid on
1
of 83 we hold a reading for · 1%
Most on one post
2
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @data_analysis_ml. 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 83 most recent posts we hold for this entry, published 31 July 2026 to 22 August 2026. 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.

Advertising

Ad load
3.61%
3 of 83 posts carry an ad marker
Regulatory tokens
3
posts carrying an erid · 3 distinct tokens
Median views · ads
3,260
over 3 measured posts
Median views · rest
3,940
over 80 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
2SDnjcHVw6K112 August 202612 August 2026
2Vtzqwno39C17 August 20267 August 2026
2W5zFG1fVN1110 August 202610 August 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 83 most recent posts we hold, published 31 July 2026 to 22 August 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

22 Aug 2026, 11:03 UTC≈1,190 views22 reactionsread 22 August 2026
Video

Чистое механическое месиво. Во время предгоночного теста перед полумарафоном гуманоидных роботов Beijing Yizhuang 2026.

🤣11🔥5💔32👍1

22 Aug 2026, 09:41 UTC≈1,310 views10 reactionsread 22 August 2026
Photo

🔥 Хочешь быстрее расти в IT? Хватит учиться в одиночку Окружение решает больше, чем кажется. Собрал папки и каналы, где можно быстрее влиться в нужное направление, следить за трендами и не вариться в своём пузыре. AI: t.me/ai_machinelearning_big_data Python: t.me/pythonl Linux: t.me/linuxacademiya Хакинг: t.me/linuxkalii DevOps: t.me/DevOPSitsec Docker: https://t.me/+90Z5TAyfuNU5YmRi Golang: t.me/Golang_google Rus

👍43🔥2💯1

22 Aug 2026, 07:12 UTC≈1,870 views11 reactionsread 22 August 2026
Photo

«NVIDIA решила ARC-AGI-3» или не совсем ? Сейчас по сети расходится громкий результат NVIDIA, но сравнение оказалось запутаннее заголовков. Результат NVIDIA получен на публичном наборе ARC-AGI-3, а не на закрытом/semi-private бенчмарке, который используется для официального leaderboard. Сам ARC Prize прямо предупреждает, что public set проще и не должен использоваться как официальный показатель прогресса. Плюс реч

6🔥3👍2

21 Aug 2026, 21:00 UTC≈2,880 views23 reactionsread 22 August 2026
Photo

⚡️ Anthropic спрятала Claude Mythos 5 внутри Claude Security Теперь обычный клиент Claude Enterprise может получить пользу от Mythos 5 через Claude Security - без прямого доступа к самой модели. Схема простая: GitHub-репозиторий → Claude Security → Mythos 5 сканирует код → на выходе уязвимости, severity, confidence и предложенные исправления. То есть Mythos 5 фактически становится специализированным security-движ

🔥136👍4

21 Aug 2026, 17:02 UTC≈3,200 views12 reactionsread 22 August 2026
Photo

OpenAI, похоже, пытается перевести пользователей ChatGPT на более жёстко измеряемое потребление На фоне жалоб, что лимиты у части пользователей начали заканчиваться быстрее, появилась версия: OpenAI постепенно балансирует бесплатное/безлимитное использование ChatGPT с более контролируемым потреблением в Codex и ChatGPT Work. Сам Tibo сообщил, что Codex уже достиг 20 млн активных пользователей, а всем пользователям

🔥6👍3🥰21

21 Aug 2026, 15:01 UTC≈3,130 views36 reactionsread 22 August 2026
Video

Я объясняю работу с ИИ друзьям

😁31🔥4💯1

21 Aug 2026, 13:49 UTC≈2,920 views11 reactionsread 22 August 2026
Photo

🔥 Python + AI без игрушечных демок. Курс для тех, кто хочет собирать рабочие системы. Stepik: «Python современный AI для разработчика и автоматизации задач» 63 урока, 382 шага, практика с кодом и автопроверкой. Внутри: RAG, tool calling, агенты, evals, MCP, Ollama, vLLM, pgvector + HNSW, безопасный text-to-SQL, prompt injection, кэш, очереди и sandbox для агентного кода. Плюс реальные автоматизации: почта, отчёты

6👍3🔥2

21 Aug 2026, 10:23 UTC≈3,050 views21 reactionsread 22 August 2026
Photo

🐳 DeepSeek показала мультимодальную Flash-модель для AI-агентов DeepSeek представила экспериментальную DeepSeek-V4-Flash-Vision-Exp — мультимодальную модель для агентов, которым нужно не только читать текст, но и понимать изображения и интерфейсы. Самое интересное — результаты на visual-agent бенчмарках: по заявленным тестам модель уже приближается к Opus 4.8, а в некоторых сценариях даже обходит её. И всё это у F

11👍7🔥3

21 Aug 2026, 09:46 UTC≈1,990 views11 reactionsread 22 August 2026
Forwarded from @ai_machinelearning_big_dataVideo

✔️ OpenAI будет ловить злоупотребления, не заглядывая в переписку Private Safety Processing - механизм для API и корпоративных клиентов, работающий по принципу нулевого хранения данных. Он разбирает серии запросов и ищет признаки злонамеренного использования, но сотрудники OpenAI при этом не видят ни промптов, ни ответов модели. Данные либо вообще не покидают периметр клиента, либо лежат на серверах OpenAI зашифров

🔥54👍2

21 Aug 2026, 09:17 UTC≈4,280 views15 reactionsread 22 August 2026
Photo

OpenAI запустила AI Futures - блог о том, как ИИ может изменить власть и общество Новый проект команды Strategic Futures посвящён не только технологиям, но и тому, что произойдёт с правами, свободой и влиянием людей, если AI станет действительно трансформирующим. Один из ключевых тезисов: главный долгосрочный риск может быть не только в самих моделях, а в концентрации власти. Автономные системы способны дать госуд

👍84🔥3

21 Aug 2026, 06:06 UTC≈2,980 views11 reactionsread 22 August 2026
Photo

⚡️ Liquid AI выпустила DSpark draft-модели для LFM2.5-1.2B-Instruct, LFM2.5-2.6B и LFM2.5-8B-A1B. Идея в speculative decoding: маленькая модель примерно на 300M параметров заранее предлагает сразу несколько токенов, а основная модель проверяет весь блок за один проход. На H100 LFM2.5-8B-A1B в MATH500 ускорилась с 428 до 1362 токенов/с — в 3,18 раза. На MacBook Pro с M4 Max LFM2.5-1.2B-Instruct в HumanEval — со 136

👍4🔥3🥰3❤‍🔥1

20 Aug 2026, 20:41 UTC≈3,500 views36 reactionsread 22 August 2026
Photo

Полный инженерный курс по AI-агентам на русском: от tool calling до production Курс инженерный, а не обзорный. Здесь почти нет рассуждений о том, «изменит ли ИИ мир», зато есть: минимальные работающие реализации каждого механизма, лабораторные с критериями приёмки, шаблоны для копирования, чек-листы перед релизом, каталог антипаттернов и набор бенчмарков, по которым можно честно сравнить две версии своего агента.

16👍13🔥7

Showing the 12 most recent of 83 posts we hold for @data_analysis_ml. 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

@data_analysis_ml 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
14 August 2026
Most recent edit
14 August 2026

Citation-graph rank

Citation-graph rank — 1,806 of 1,584,142entries 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Data Science by ODS.ai 🦜
@opendatascience · 39,039
5 posts
Технозаметки Малышева
@tsingular · 11,821
4 posts
Machinelearning
@ai_machinelearning_big_data · 284,523
3 posts
IT мемы | Мемы программиста
@memes_prog · 6,249
3 posts
Cherry RAiT's blog
@Talyutin · 27
3 posts
AI Monitor All
@aimonitorall · 13
2 posts
Artificial Intelligence
@ArtificialIntelligencedl · 16,784
2 posts
Математика Дата саентиста
@data_math · 14,134
2 posts
NOVA | AI Hub
@nova_ai_hub · 16
2 posts
TensorFlow
@tensorflowblog · 1,348
2 posts
Generative AI
@ai_generative · 2,188
1 post
Big Data AI
@bigdatai · 18,149
1 post
Клуб CDO
@cdo_club · 4,044
1 post
Библиотека С# С++
@cpluscsharp · 10,054
1 post
C# (C Sharp) programming
@csharp_ci · 18,130
1 post
Аналитик данных
@dataanlitics · 6,207
1 post
Prog books
@frontendbooksit · 12,694
1 post
Data360.ru
@fsecrets · 82
1 post
Github
@github_code · 2,518
1 post
🧤 Повод задуматься. Валерия Гулимова
@green_shorts · 364
1 post
Frontend Hash
@hashdev · 3,238
1 post
Тест Артьюринга
@innovatorsway · 1,504
1 post
Javascript
@javascriptv · 17,192
1 post
Сергей Кадомский - про коммуникацию, психологию и cultural intelligence в жизни, бизнесе и IT
@kadomsky · 1,217
1 post
Кадровый Болт Генона
@kadr_b0lt_Genona · 2,016
1 post
Kazarin.online
@kazarin_online · 636
1 post
Кроля говорит — надо смотреть!
@krolya_says · 1,444
1 post
Машиннное обучение | Наука о данных Библиотека
@machinelearning_books · 16,837
1 post
MaxRepost
@maxrepost · 1,362
1 post
Менделеевщина!
@mendeleevshina · 23,388
1 post
Mrs Wallbreaker
@MrsWallbreaker · 1,052
1 post
Одержимый ИИ
@ObsessedAI · 18
1 post
Полезеные материалы
@polezniy_mat · 1
1 post
Пока без названия
@timurhdv · 226
1 post
very vibe coding
@veryvibecoding · 113
1 post
Вайб-крафтинг
@VibeCrafting · 64
1 post
Искусственный интеллект. Высокие технологии
@vistehno · 72,222
1 post
Владимир Ломтев блог
@vladimirexp · 617
1 post
White Tensor [AI, ML, DL]
@white_tensor · 161
1 post

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 53 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

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.

Python/ django
@pythonl · 58,935
Telegram ranks this channel #2 of 84 here — alongside 83 others — read 22 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 72,222
Telegram ranks this channel #2 of 94 here — alongside 93 others — read 20 August 2026
Machinelearning
@ai_machinelearning_big_data · 284,523
Telegram ranks this channel #4 of 95 here — alongside 94 others — read 10 August 2026
XOR
@xor_journal · 152,006
Telegram ranks this channel #19 of 93 here — alongside 92 others — read 12 August 2026
Data Secrets
@data_secrets · 92,304
Telegram ranks this channel #23 of 98 here — alongside 97 others — read 17 August 2026
Простой Python | Программирование
@python_piton_javascript · 128,051
Telegram ranks this channel #50 of 84 here — alongside 83 others — read 13 August 2026
Однажды в трендах
@trendo · 68,975
Telegram ranks this channel #56 of 90 here — alongside 89 others — read 20 August 2026
Physics.Math.Code
@physics_lib · 145,896
Telegram ranks this channel #59 of 72 here — alongside 71 others — read 13 August 2026
IT Portal
@IT_Portal · 101,184
Telegram ranks this channel #63 of 78 here — alongside 77 others — read 15 August 2026
[PYTHON:TODAY]
@python2day · 63,879
Telegram ranks this channel #83 of 91 here — alongside 90 others — read 21 August 2026
Google Таблицы
@google_sheets · 60,766
Telegram ranks this channel #94 of 98 here — alongside 97 others — read 22 August 2026

This channel appears in 11 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 22 August 2026 — this entry's latest reading, not the date you are reading this.

“Анализ данных (Data analysis)” (@data_analysis_ml), 50,530 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/data_analysis_ml.

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.