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Channel

Data Science

@datascienceiot

On this record: Topic · Growth · Engagement · What this channel posts · Advertising · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

42,496subscribers

+254 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-1001131189982
TypeChannel
Username@datascienceiot
DescriptionDS По всем вопросам- @haarrp @ai_machinelearning_big_data - machine learning @pythonl - Python @itchannels_telegram - 🔥 best it channels @ArtificialIntelligencedl - AI @pythonlbooks-📚 @programming_books_it -📚 Реестр РКН: https://clck.ru/3Fk3zS
Created26 July 2017 — measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live10 November 2026
Measurements held62
Confirmed unchanged1 time, most recently 10 November 2026
On Telegramt.me/datascienceiot

Topic

Education — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 95% 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

42,23342,65542,44442,4966 August 202610 November 2026
62 measurements spanning 96 days, net +254. 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 42,170–42,718 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)SubscribersChange
10 Nov 2026, 08:5142,496-17
8 Nov 2026, 19:2042,513-17
7 Nov 2026, 11:2142,530-10
6 Nov 2026, 10:3942,540-9
5 Nov 2026, 10:0742,549-1
4 Nov 2026, 07:2642,550-18
3 Nov 2026, 05:2942,568-7
2 Nov 2026, 03:2142,575-7
1 Nov 2026, 00:1642,582-4
30 Oct 2026, 03:1942,586-6
28 Oct 2026, 23:5542,592-12
27 Oct 2026, 23:5542,604-21
27 Oct 2026, 00:0942,625-11
25 Oct 2026, 21:0142,636-5
24 Oct 2026, 21:5042,641-8
23 Oct 2026, 20:2842,649+3
22 Oct 2026, 21:1942,646+17
21 Oct 2026, 14:3742,629+73
20 Oct 2026, 13:1642,556+9
18 Oct 2026, 19:2642,547first reading

Engagement

81 posts held, back to 7 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 194 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.10%
avg views ÷ 42,496 subscribers
Avg views / post
2,590
19 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
19
of 81 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 10 November 2026
Posts held81 (7 July 2026 – 10 November 2026)
Views total49,280
Reactions total—
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Nov 2026, 22:41 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
≈1,790
Videos
≈5
Links
≈2,180

Lifetime counters from Telegram’s own channel header, read 10 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
1m 04s
Average length
32s

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.

Advertising

Ad load
9.88%
8 of 81 posts carry an ad marker
Regulatory tokens
8
posts carrying an erid · 8 distinct tokens
Median views · ads
3,020
over 8 measured posts
Median views · rest
3,450
over 73 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. They are printed side by side with the count behind each rather than as a ratio: an ad and an ordinary post are not otherwise matched — for topic, for length, for hour of day — so the gap between them is a description of two groups and not the effect of one being an ad.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2SDnjezu8Km121 September 202621 September 2026
2VSb5weurkr124 September 202624 September 2026
2VtzqvCaFkz110 November 202610 November 2026
2VtzqxCfpUj121 August 202621 August 2026
2VtzqxQZmyv125 September 202625 September 2026
2W5zFGRNGWm116 July 202616 July 2026
2W5zFGXZQLy17 October 20267 October 2026
2W5zFJwEKww118 August 202618 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 81 most recent posts we hold, published 7 July 2026 to 10 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: 1 of 19 posts held from the last 30 days (5.26%) 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).

10 Nov 2026, 12:15 UTC≈1,010 viewsread 10 November 2026
Photo

Claude решил задачу по физике чёрных дыр, которую не могли закрыть около 20 лет Anthropic опубликовала исследование, в котором внутренняя исследовательская модель Claude получила новый результат в теоретической физике. Работа посвящена переходу Хокинга - Пейджа. Это фазовый переход, связанный с термодинамикой чёрных дыр в пространстве анти-де Ситтера (AdS). Исследователей интересовал вопрос: сохраняется ли этот пе…

10 Nov 2026, 10:14 UTC≈1,160 viewsread 10 November 2026
Advertisementerid 2VtzqvCaFkzPhoto

🔍 Открытое ML-собеседование с техлидом Яндекса| 12 ноября, 19:00 мск Приходи онлайн посмотреть, как проходит техническое интервью на ML-инженера, и попробуй ответить на вопросы вместе с кандидатом Как всё будет проходить: 📂 Интервьюер: Любовь Чубарова, техлид в Яндексе (RnD Alice AI), одна из первых сотрудниц YandexArt, преподаватель ВШЭ, экс-руководитель аналитики Центра ИИ Сколтеха. В роли кандидата – инженер-до…

9 Nov 2026, 18:35 UTC≈1,350 viewsread 10 November 2026
Photo

Yoshua Bengio and collaborators just released a goldmine 182-page survey on mechanistic interpretability! "Understanding AI from the Inside" 📓 Read @datascienceiot

5 Nov 2026, 11:10 UTC≈2,390 viewsread 10 November 2026
Photo

A Circuit for In-Context Learning 📓 Read @datascienceiot

5 Nov 2026, 09:03 UTC≈2,230 viewsread 10 November 2026
Photo

Алгоритм знает, где вы будете 7-го ноября 😎 RecSys-митап в Москве для тех, кто уже строит рекомендательные системы и хочет делать это еще лучше. В программе — доклады от топовых экспертов Сбера с разбором кейсов, свежих подходов и неочевидных решений. После официальной части — нетворкинг. Время в узком кругу профессионалов и сообщества Зеленый RecSys. Участие бесплатное, но количество мест ограничено. Москва. Су…

27 Oct 2026, 18:41 UTC≈3,450 viewsread 10 November 2026
Photo

"Large Flow Language Models" What if we could turn existing LLMs into diffusionLMs that generate multiple tokens in parallel without losing accuracy? 📓 Read @datascienceiot

26 Oct 2026, 11:16 UTC≈3,230 viewsread 10 November 2026
Photo

Бесплатная книга о больших языковых моделях – 315 страниц от предобучения до рассуждений. Foundations of Large Language Models Тун Сяо и Цзинбо Чжу системно объясняет, как устроены LLM, как их обучают и применяют. Внутри шесть основных тем: - Предобучение: задачи обучения и архитектуры моделей. - Генеративные модели: Transformer, подготовка данных, масштабирование и длинный контекст. - Промптинг: обучение на приме…

25 Oct 2026, 10:12 UTC≈2,520 viewsread 10 November 2026
Photo

Working with Agentic `Teammates': When a New Organizational Actor Collides with the Human Ecosystem of Work 📓 Read @datascienceiot

23 Oct 2026, 11:39 UTC≈2,760 viewsread 10 November 2026
Photo

The Geometry of Agent Memory: Forecasting Retrieval-Bound Memory Failures, and Characterizing Its Limits 📓 Read @datascienceiot

22 Oct 2026, 13:28 UTC≈2,760 viewsread 10 November 2026
Photo

At the Limits of Computability: Steps Towards Autonomous AI Discovery on the Busy Beaver Frontier 📓 Read @datascienceiot

21 Oct 2026, 17:45 UTC≈2,900 viewsread 10 November 2026
Photo

Patch the Planet: global response coordination as agents uncover critical vulnerabilities https://openai.com/index/coordinated-disclosure-of-critical-vulnerabilities/ @datascienceiot

Showing the 12 most recent of 81 posts we hold for @datascienceiot. 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 8 posts on @datascienceiot 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
21 August 2026
Most recent seen missing
3 November 2026
Median time before seen missing
8 days
Seen missing in the last 30 days
2

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 5 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.

Machinelearning
@ai_machinelearning_big_data · 275,659
#1
Машиннное обучение | Наука о данных Библиотека
@machinelearning_books · 16,955
#2
Анализ данных (Data analysis)
@data_analysis_ml · 51,923
#3
Математика Дата саентиста
@data_math · 14,419
#4
Python/ django
@pythonl · 58,287
#5
Machine learning Interview
@machinelearning_interview · 30,560
#6
Big Data AI
@bigdatai · 18,329
#7
Машинное обучение RU
@machinelearning_ru · 18,339
#8
Artificial Intelligence
@ArtificialIntelligencedl · 16,815
#9
Data Secrets
@data_secrets · 96,035
#10
Data Science. SQL hub
@sqlhub · 36,025
#11
Python вопросы с собеседований
@python_job_interview · 24,906
#12
Аналитик данных
@dataanlitics · 6,386
#13
Data Science | Machinelearning [ru]
@devsp · 19,659
#14
Data Science Jobs
@datascienceml_jobs · 21,642
#15
Neural Networks | Нейронные сети
@neural · 11,724
#16
DeepSchool
@deep_school · 10,723
#17
Искусственный интеллект. Высокие технологии
@vistehno · 70,139
#18
Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение
@dsproglib · 18,290
#19
Java Books
@java_library · 14,048
#20
Машинное обучение. Книги по программированию
@maschinelearning · 10,849
#21
Библиотека С# С++
@cpluscsharp · 10,015
#22
Golang Books
@golang_books · 16,863
#23
Physics.Math.Code
@physics_lib · 146,676
#24
Data jobs — вакансии по data science, анализу данных, аналитике, искусственному интеллекту
@datajob · 15,139
#25
Computer Science and Programming
@computer_science_and_programming · 138,623
#26
Python RU
@pro_python_code · 12,302
#27
Yandex for ML
@yandexforml · 19,136
#28
Нескучный Data Science
@not_boring_ds · 12,081
#29
Время Валеры
@cryptovalerii · 32,082
#30
Machine Learning
@MachineLearning9 · 41,912
#31
Библиотека собеса по Data Science | вопросы с собеседований
@ds_interview_lib · 4,459
#32
BZD • Книги для программистов
@bzd_channel · 36,213
#33
Библиотека задач по Data Science | тесты, код, задания
@ds_problems_lib · 3,966
#34
ODS #jobs
@odsjobs · 14,582
#35
Denis Sexy IT 🤖
@denissexy · 140,753
#36
C++ Academy
@cpluspluc · 15,457
#37
Dealer.AI
@dealerAI · 17,113
#38
Data Science & Machine Learning
@datasciencefun · 77,697
#39
hahacker_news
@hahacker_news · 25,231
#40
Machine Learning with Python
@CodeProgrammer · 68,478
#41
Python Jobs
@python_djangojobs · 15,125
#42
Инжиниринг Данных
@rockyourdata · 23,685
#43
Институт AIRI
@airi_research_institute · 13,977
#44
Data Science Jobs
@datasciencejobs · 22,587
#45
AI & ML Papers
@PaperNexus · 34,361
#46
Machine Learning & Artificial Intelligence | Data Science Free Courses
@datasciencefree · 68,644
#47
Django Python
@Django_pythonl · 6,573
#48
Data Science Projects
@pythonspecialist · 56,410
#49
Start Career in DS
@start_ds · 11,463
#50
DataFrog: Data Science
@datasfrog · 1,829
#51
🏄 Соревновательный Data Science | Kaggle | Чемпионаты
@data_science_winners · 3,366
#52
🏆 AIeron | Data Feeling
@datafeeling · 14,208
#53
DATApedia | Data science
@ds_wiki · 3,183
#54
Just links
@j_links · 6,943
#55
Machine Learning | Нейронные сети, ИИ, Big Data
@ML_secrets · 7,365
#56
Библиотека питониста | Python, Django, Flask
@pyproglib · 36,972
#57
Библиотека программиста
@proglibrary · 77,612
#58
Жёлтый AI
@zheltyi_ai · 9,371
#59
Rust
@rust_code · 9,152
#60
Artificial Intelligence && Deep Learning
@DeepLearning_ai · 56,955
#61
эйай ньюз
@ai_newz · 98,262
#62
DevOps
@DevOPSitsec · 23,892
#63
Golang
@Golang_google · 40,453
#64
Сиолошная
@seeallochnaya · 81,254
#65
Техножрица 👩‍💻👩‍🏫👩‍🔧
@tech_priestess · 15,110
#66
Learn Python Coding
@pythonRe · 40,901
#67
Artificial Intelligence
@Artificial_intelligence_in · 65,715
#68
Градиент обреченный
@doomgrad · 8,840
#69
Kali Linux
@linuxkalii · 55,842
#70
New Yorko Times
@new_yorko_times · 10,720
#71
Data Analytics
@DataAnalyticsX · 30,880
#72
PHP Academy
@phpshka · 9,131
#73
LLM под капотом
@llm_under_hood · 30,219
#74
DLStories
@dl_stories · 15,546
#75
Kali Novskaya
@rybolos_channel · 19,136
#76

Read from Telegram’s recommendation API, most recently 29 August 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.

Physics.Math.Code
@physics_lib · 146,676
Telegram ranks this channel #6 of 72 here — alongside 71 others — read 13 August 2026
DataFlair
@dataflair · 18,577
Telegram ranks this channel #7 of 83 here — alongside 82 others — read 4 October 2026
Python/ django
@pythonl · 58,287
Telegram ranks this channel #7 of 84 here — alongside 83 others — read 22 August 2026
Computer Science and Programming
@computer_science_and_programming · 138,623
Telegram ranks this channel #7 of 87 here — alongside 86 others — read 13 August 2026
Data Science | Machinelearning [ru]
@devsp · 19,659
Telegram ranks this channel #10 of 91 here — alongside 90 others — read 30 September 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,923
Telegram ranks this channel #10 of 93 here — alongside 92 others — read 25 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 70,139
Telegram ranks this channel #10 of 94 here — alongside 93 others — read 20 August 2026
Data Science. SQL hub
@sqlhub · 36,025
Telegram ranks this channel #11 of 87 here — alongside 86 others — read 2 September 2026
Python вопросы с собеседований
@python_job_interview · 24,906
Telegram ranks this channel #15 of 90 here — alongside 89 others — read 15 September 2026
Machinelearning
@ai_machinelearning_big_data · 275,659
Telegram ranks this channel #17 of 95 here — alongside 94 others — read 10 August 2026
Python Books. Книги по питону
@pythonbooks · 38,331
Telegram ranks this channel #19 of 65 here — alongside 64 others — read 17 September 2026
Machine Learning
@MachineLearning9 · 41,912
Telegram ranks this channel #23 of 79 here — alongside 78 others — read 30 August 2026
Data Science Jobs
@datascienceml_jobs · 21,642
Telegram ranks this channel #25 of 97 here — alongside 96 others — read 24 September 2026
Artificial Intelligence && Deep Learning
@DeepLearning_ai · 56,955
Telegram ranks this channel #25 of 87 here — alongside 86 others — read 23 August 2026
Machine Learning with Python
@CodeProgrammer · 68,478
Telegram ranks this channel #30 of 84 here — alongside 83 others — read 20 August 2026
Machine learning Interview
@machinelearning_interview · 30,560
Telegram ranks this channel #31 of 98 here — alongside 97 others — read 7 September 2026
ML - DS/DA/DE - AI [Jobs, InterviewPrep] 🇮🇳
@ml_ds_ai_jobs · 25,720
Telegram ranks this channel #33 of 81 here — alongside 80 others — read 13 September 2026
AI & ML Papers
@PaperNexus · 34,361
Telegram ranks this channel #33 of 85 here — alongside 84 others — read 4 September 2026
Programming, data science, ML - free courses by Big Data Specialist
@bigdataspecialist · 26,239
Telegram ranks this channel #37 of 80 here — alongside 79 others — read 12 September 2026
Machine Learning & Artificial Intelligence | Data Science Free Courses
@datasciencefree · 68,644
Telegram ranks this channel #43 of 88 here — alongside 87 others — read 20 August 2026
Data Science Portfolio - Kaggle Datasets & AI Projects | Artificial Intelligence
@DataPortfolio · 37,776
Telegram ranks this channel #45 of 83 here — alongside 82 others — read 31 August 2026
Data Science Projects
@pythonspecialist · 56,410
Telegram ranks this channel #45 of 89 here — alongside 88 others — read 23 August 2026
Codehub
@pythonadvisorai · 31,362
Telegram ranks this channel #46 of 71 here — alongside 70 others — read 5 September 2026
Pythonist.ru - образование по питону
@pythonist_ru · 23,873
Telegram ranks this channel #48 of 82 here — alongside 81 others — read 17 September 2026

This channel appears in 47 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 10 November 2026 — this entry's latest reading, not the date you are reading this.

“Data Science” (@datascienceiot), 42,496 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/datascienceiot.

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.