Telegram RegisterThe public register of Telegram
Telegram profile photo for Нескучный Data Science

Channel

Нескучный Data Science

@not_boring_ds

On this record: Topic · Growth · Engagement · Reactions · Stars · Advertising · Posts · Citations · Telegram's recommendations · Cite this entry

12,052subscribers

+105 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001680781925
TypeChannel
Username@not_boring_ds
Created17 February 2022measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded7 August 2026
Last confirmed live17 September 2026
Measurements held29
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/not_boring_ds

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 11 September 2026 and assigned it the closest of 31 fixed categories, at 43% 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 why it has no browse page of its own yet.

Growth

11,94612,05612,0017 August 2026 — 11,947 subscribers7 August 2026 — 11,952 subscribers8 August 2026 — 11,950 subscribers9 August 2026 — 11,946 subscribers10 August 2026 — 11,954 subscribers11 August 2026 — 11,991 subscribers12 August 2026 — 11,999 subscribers14 August 2026 — 12,003 subscribers15 August 2026 — 12,012 subscribers17 August 2026 — 12,011 subscribers18 August 2026 — 12,013 subscribers19 August 2026 — 12,017 subscribers20 August 2026 — 12,036 subscribers22 August 2026 — 12,039 subscribers24 August 2026 — 12,050 subscribers25 August 2026 — 12,045 subscribers26 August 2026 — 12,040 subscribers27 August 2026 — 12,044 subscribers28 August 2026 — 12,055 subscribers29 August 2026 — 12,056 subscribers30 August 2026 — 12,053 subscribers1 September 2026 — 12,050 subscribers2 September 2026 — 12,055 subscribers4 September 2026 — 12,047 subscribers6 September 2026 — 12,044 subscribers10 September 2026 — 12,046 subscribers12 September 2026 — 12,040 subscribers15 September 2026 — 12,043 subscribers17 September 2026 — 12,052 subscribers12,0527 August 202617 September 2026
29 measurements spanning 42 days, net +105. 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 11,930–12,073 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 29
Measured (UTC)SubscribersChange
17 Sept 2026, 20:3912,052+9
15 Sept 2026, 15:0112,043+3
12 Sept 2026, 06:3812,040-6
10 Sept 2026, 02:1812,046+2
6 Sept 2026, 20:1912,044-3
4 Sept 2026, 10:1412,047-8
2 Sept 2026, 19:5512,055+5
1 Sept 2026, 16:2212,050-3
30 Aug 2026, 11:5712,053-3
29 Aug 2026, 08:2812,056+1
28 Aug 2026, 09:2812,055+11
27 Aug 2026, 11:4512,044+4
26 Aug 2026, 09:4812,040-5
25 Aug 2026, 09:4512,045-5
24 Aug 2026, 09:2412,050+11
22 Aug 2026, 17:5612,039+3
20 Aug 2026, 08:1212,036+19
19 Aug 2026, 11:3412,017+4
18 Aug 2026, 13:4612,013+2
17 Aug 2026, 11:1812,011first reading

Engagement

23 posts held, back to 13 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 48 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
20.1%
avg views ÷ 12,052 subscribers
Avg views / post
2,430
3 posts measured
Reaction rate
1.43%
reactions ÷ views · ER floor
Posts in window
3
of 23 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 29 August 2026
Posts held23 (13 June 202629 August 2026)
Views total7,280
Reactions total104
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken2 Sept 2026, 23:14 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.

Reaction mix

890 reactions across 23 posts, in 20 distinct kinds. The most used accounts for 24.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥21924.6%
18020.2%
🤣11412.8%
👍10311.6%
👎728.09%
🐳546.07%
🎉364.04%
343.82%
😁192.13%
💯161.80%
😱101.12%
🙈91.01%
🤔80.899%
🦄40.449%
🗿30.337%
🥰30.337%
🤯20.225%
🤷20.225%
👌10.112%
🙏10.112%

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 23 of the 23 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 890 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 23 most recent posts we hold, published 13 June 2026 to 29 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
2
of 23 we hold a reading for · 9%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @not_boring_ds. 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 23 most recent posts we hold for this entry, published 13 June 2026 to 29 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
4.35%
1 of 23 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
3,870
over 1 measured post
Median views · rest
3,730
over 22 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
2VtzqwwQoy412 August 20262 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 23 most recent posts we hold, published 13 June 2026 to 29 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

29 Aug 2026, 12:55 UTC≈2,020 views32 reactionsread 2 September 2026

🤣 Как за год заработать банку 50 тысяч 👼 После того как я стал руководителем, мне хотелось решить как можно больше задач силами своей команды. Мы умели работать с текстами, и эту экспертизу хотелось применить в продуктах банка. 📈 Одна такая задача нашлась в инвестиционном продукте. Новости без категорий было неудобно читать. По крайней мере, так казалось мне — человеку, который умел их классифицировать. Решение выг

🤣187🐳6🤔1

26 Aug 2026, 15:45 UTC≈2,680 views47 reactionsread 2 September 2026
Photo

✈️ Альфа оплатит до 20 000 рублей на обеды состоятельным сотрудникам Сбера 🍽 У премиальных клиентов Альфа-Банка есть привилегия: банк компенсирует еду в ресторанах российских аэропортов. Чтобы не заключать договор с каждым заведением вручную, Альфа подключила дата-сайентистов 👨‍💻 Как рассказали в статье на РБК, алгоритм анализирует карточные операции, сопоставляет их с координатами терминалов и определяет, прошла л

🤣39😱4🔥3🐳1

25 Aug 2026, 11:25 UTC≈2,580 views25 reactionsread 2 September 2026

🐍 Как сделать автоматизацию поддержки 100% одной фразой 🎤 В 2018 году в одной крупной компании проходила презентация чат-бота. Команда защищала метрику автоматизации. Один из топ-менеджеров выслушал доклад и сказал: — Я знаю, как одной фразой довести вашу автоматизацию до 100%. 📊 В 2020 году уже в другой крупной компании топ-менеджера уволили за то, что он слишком успешно растил автоматизацию. Автоматизацию раст

🔥14🤣54🐳1👎1

21 Aug 2026, 14:48 UTC≈3,250 views17 reactions1 Starread 2 September 2026
Forwarded from @bigdatateamPhoto

🚀 50 грантов Tech Orda: специализация AI Agents Engineer Уникальная возможность для граждан РК от 18 до 45 лет: 1. Получить грант 400 000 ₸ от государства на обучение в IT; 2. С вероятностью 60+% достичь карьерных целей в ближайшие 6 месяцев при обучении с BigData Team. 📌 Как подать заявку? До 6 сентября: 1. Нажать "подать заявку" на портале Astana Hub 2. Зарегистрироваться и пройти тестирование на Learn BDT 3. Под

7👍4🥰3🐳2🗿1

17 Aug 2026, 06:11 UTC≈3,870 views62 reactionsread 2 September 2026
Photo

🤣 Яндекс сам себя забанил Помните, я писал, как Тинькофф защитил меня от собственного спама? Похоже, тг-боты Яндекса это прочитали, решили повторить успех и применили тот же подход к рекламе. 🍽 Хотел купить рекламу для @mirabistro на Яндекс Картах. Написал в чат-бот поддержки. Бот объяснил, что нужно отправить письмо на указанный им адрес, добавить номер телефона и логин — всё сделал по инструкции. ✉️ Причём для

🤣49😁64🐳1👍1🔥1

16 Aug 2026, 07:03 UTC≈3,360 views76 reactionsread 2 September 2026
Photo

🧠 10 бит в секунду, или Почему люди тупые Когда я учился в университете, мой сосед любил повторять: — Люди тупые. В том числе и я. Вторая часть фразы нравилась мне гораздо больше первой. В ней была полезная мысль: свои когнитивные ограничения лучше учитывать заранее, а не обнаруживать постфактум. 💾 Позже я попал к научному руководителю, у которого одновременно со мной было ещё несколько десятков студентов. Он чес

🔥4318👍12🐳2💯1

11 Aug 2026, 10:04 UTC≈3,730 views43 reactionsread 2 September 2026
Photo

Конференция Ozon Tech, уже успевшая заслужить высокоранговую славу, обещает и в этом году собрать много интересного для тех, кто работает с ML&DS. Программа E-CODE 2026 еще пополняется, но трек уже выглядит вполне серьезно: сложный индустриальный ML, генеративные подсказки, уровни дообучения и агентский Cotype. Такое нам определенно надо. Еще и участие бесплатное - осталось только зарегистрироваться: https://ecode.o

15🔥11🎉9👍2👎2🤣2🐳1🤷1

11 Aug 2026, 06:03 UTC≈3,600 views19 reactionsread 2 September 2026
Photo

ИИ крадёт у нас или учится у нас? 🧠 Недавно сидел на панельной дискуссии. Во время вопросов из зала прозвучало примерно следующее: — Как быть с тем, что ИИ будет обучаться на наших данных? Как защитить то уникальное, на создание чего человек потратил столько времени? Но тут возникает неудобный вопрос: а в чём именно заключается эта уникальность? Я люблю сравнивать работу ИИ с ЕИ — естественным интеллектом. Такое

12🔥3👎2🐳1💯1

9 Aug 2026, 08:10 UTC≈3,420 views39 reactionsread 2 September 2026

Как понять по письму, что задача не выполнена? 📨 За годы работы в крупных компаниях мне пришлось прочитать очень много писем. Иногда их приходит до сотни в день. Поэтому навыки анализа данных приходится применять и здесь. Представьте: вы поставили кому-то задачу, подошёл срок — и вам присылают отчёт. Это может быть один абзац, а может быть целый лист А4. Вы читаете про процесс, коллег, сложности и то, как все герои

🔥21💯10🐳42🗿2

8 Aug 2026, 13:03 UTC≈2,550 views21 reactionsread 2 September 2026
Forwarded from @rads_ai

На конференциях только и разговоров, что об агентах. Вообще, я бы назвал это harness'ами. Они могут приносить кучу пользы, и их огромное количество: Claude Code, Codex, pi, Hermes, OpenClaw, Cursor, Muse Code... Хорошая новость в том, что под капотом +- одни и те же механизимы, и если в них разобраться, почти не важно, какой harness у вас под рукой. Поэтому проведу в понедельник, 10 августа в 18:30 открытый вебина

🔥11👍54🐳1

7 Aug 2026, 19:37 UTC≈3,040 views35 reactionsread 2 September 2026
Photo

❓ Научитесь отвечать на вопрос «зачем?», прежде чем ставить задачу ИИ Моё знакомство с Codex началось, когда появилась вполне конкретная задача: собрать сайт для @mirabistro. Сайты я делал и раньше — первый написал на PHP ещё в восьмом классе. Но никогда не вайбкодил и относился к этому довольно скептически. Несмотря на десять лет работы в анализе данных, мне казалось, что нормальный рабочий продукт всё равно прид

👍226🔥4🐳1💯1🤷1

6 Aug 2026, 16:04 UTC≈2,980 views25 reactionsread 2 September 2026

🔥 ODS Moscow × Нескучный Data Science: бранч в эту субботу После поста про МИРА можно уже не делать вид, что выбор места — случайное совпадение и не очень нативная рекламная интеграция 😅 В эту субботу снова собираемся там на офлайн-бранч вместе с ODS Moscow. Будем знакомиться, есть и обсуждать ИИ, Data Science, карьеру и собственный бизнес. Заодно можно будет посмотреть на тот самый «очень дорогой pet-проект» из п

👍11🔥73👎21🐳1

Showing the 12 most recent of 23 posts we hold for @not_boring_ds. 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.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 2 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.

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.

Время Валеры
@cryptovalerii · 30,829
Telegram ranks this channel #7 of 94 here — alongside 93 others — read 6 September 2026
karpov.courses
@KarpovCourses · 27,430
Telegram ranks this channel #8 of 96 here — alongside 95 others — read 10 September 2026
Dev & ML Connectable Jobs
@dev_connectablejobs · 27,750
Telegram ranks this channel #11 of 94 here — alongside 93 others — read 10 September 2026
Machine learning Interview
@machinelearning_interview · 30,308
Telegram ranks this channel #11 of 98 here — alongside 97 others — read 7 September 2026
Анализ данных (Data analysis)
@data_analysis_ml · 50,631
Telegram ranks this channel #14 of 93 here — alongside 92 others — read 25 August 2026
Stepik – онлайн-курсы
@stepik_courses · 24,445
Telegram ranks this channel #16 of 93 here — alongside 92 others — read 16 September 2026
Machinelearning
@ai_machinelearning_big_data · 280,660
Telegram ranks this channel #19 of 95 here — alongside 94 others — read 10 August 2026
Data Secrets
@data_secrets · 93,800
Telegram ranks this channel #20 of 98 here — alongside 97 others — read 17 August 2026
gonzo-обзоры ML статей
@gonzo_ML · 24,323
Telegram ranks this channel #28 of 93 here — alongside 92 others — read 16 September 2026
Data Science
@datascienceiot · 42,642
Telegram ranks this channel #29 of 76 here — alongside 75 others — read 29 August 2026
Alfa Digital
@alfadigital_jobs · 54,393
Telegram ranks this channel #29 of 99 here — alongside 98 others — read 24 August 2026
LLM под капотом
@llm_under_hood · 29,146
Telegram ranks this channel #30 of 96 here — alongside 95 others — read 9 September 2026
Яндекс Образование
@Education_Yandex · 37,959
Telegram ranks this channel #30 of 96 here — alongside 95 others — read 31 August 2026
XOR
@xor_journal · 175,669
Telegram ranks this channel #30 of 93 here — alongside 92 others — read 12 August 2026
Яндекс нанимает | Вакансии для разработчиков
@ya_jobs · 32,756
Telegram ranks this channel #31 of 96 here — alongside 95 others — read 5 September 2026
Инжиниринг Данных
@rockyourdata · 23,767
Telegram ranks this channel #33 of 93 here — alongside 92 others — read 17 September 2026
Job for Analysts & Data Scientists
@foranalysts · 36,643
Telegram ranks this channel #33 of 96 here — alongside 95 others — read 1 September 2026
эйай ньюз
@ai_newz · 96,889
Telegram ranks this channel #33 of 94 here — alongside 93 others — read 16 August 2026
LEFT JOIN
@leftjoin · 42,064
Telegram ranks this channel #37 of 95 here — alongside 94 others — read 29 August 2026
Reveal the Data
@revealthedata · 27,839
Telegram ranks this channel #38 of 96 here — alongside 95 others — read 10 September 2026
настенька и графики
@nastengraph · 28,213
Telegram ranks this channel #40 of 94 here — alongside 93 others — read 9 September 2026
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 45,274
Telegram ranks this channel #41 of 90 here — alongside 89 others — read 28 August 2026
Python вопросы с собеседований
@python_job_interview · 24,887
Telegram ranks this channel #42 of 90 here — alongside 89 others — read 15 September 2026
Yandex for Developers
@Yandex4Developers · 28,505
Telegram ranks this channel #42 of 94 here — alongside 93 others — read 9 September 2026

This channel appears in 31 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 17 September 2026 — this entry's latest reading, not the date you are reading this.

“Нескучный Data Science” (@not_boring_ds), 12,052 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/not_boring_ds.

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.