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Channel

Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение

@dsproglib

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

18,290subscribers

-116 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1001191313451
TypeChannel
Username@dsproglib
DescriptionВсе самое полезное для дата сайентиста в одном канале. Учиться у нас: clc.to/6qVHgg По рекламе: @tproger_sales_bot Для обратной связи: @proglibrary_feeedback_bot РКН: https://gosuslugi.ru/snet/67a5b03124c8ba6dcaa121c9
Created23 July 2018 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live9 November 2026
Measurements held57
Confirmed unchanged1 time, most recently 9 November 2026
On Telegramt.me/dsproglib

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 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

18,29018,41018,3506 August 2026 — 18,406 subscribers6 August 2026 — 18,406 subscribers7 August 2026 — 18,407 subscribers7 August 2026 — 18,410 subscribers8 August 2026 — 18,409 subscribers9 August 2026 — 18,408 subscribers11 August 2026 — 18,407 subscribers12 August 2026 — 18,402 subscribers13 August 2026 — 18,401 subscribers14 August 2026 — 18,397 subscribers16 August 2026 — 18,391 subscribers17 August 2026 — 18,388 subscribers18 August 2026 — 18,393 subscribers19 August 2026 — 18,389 subscribers20 August 2026 — 18,386 subscribers21 August 2026 — 18,385 subscribers23 August 2026 — 18,380 subscribers24 August 2026 — 18,375 subscribers25 August 2026 — 18,371 subscribers26 August 2026 — 18,368 subscribers27 August 2026 — 18,369 subscribers28 August 2026 — 18,370 subscribers29 August 2026 — 18,372 subscribers31 August 2026 — 18,376 subscribers1 September 2026 — 18,372 subscribers2 September 2026 — 18,370 subscribers3 September 2026 — 18,363 subscribers9 September 2026 — 18,352 subscribers11 September 2026 — 18,356 subscribers13 September 2026 — 18,346 subscribers15 September 2026 — 18,342 subscribers17 September 2026 — 18,340 subscribers19 September 2026 — 18,335 subscribers26 September 2026 — 18,339 subscribers4 October 2026 — 18,331 subscribers9 October 2026 — 18,335 subscribers14 October 2026 — 18,334 subscribers16 October 2026 — 18,329 subscribers17 October 2026 — 18,326 subscribers18 October 2026 — 18,324 subscribers20 October 2026 — 18,320 subscribers21 October 2026 — 18,322 subscribers22 October 2026 — 18,314 subscribers23 October 2026 — 18,308 subscribers24 October 2026 — 18,304 subscribers25 October 2026 — 18,300 subscribers28 October 2026 — 18,308 subscribers29 October 2026 — 18,311 subscribers30 October 2026 — 18,309 subscribers31 October 2026 — 18,310 subscribers1 November 2026 — 18,308 subscribers2 November 2026 — 18,306 subscribers3 November 2026 — 18,300 subscribers4 November 2026 — 18,298 subscribers5 November 2026 — 18,299 subscribers8 November 2026 — 18,298 subscribers9 November 2026 — 18,290 subscribers6 August 20269 November 2026
57 measurements spanning 95 days, net -116. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 18,272–18,428 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 57
Measured (UTC)SubscribersChange
9 Nov 2026, 14:5118,290-8
8 Nov 2026, 10:1618,298-1
5 Nov 2026, 00:2518,299+1
4 Nov 2026, 02:1818,298-2
3 Nov 2026, 05:1718,300-6
2 Nov 2026, 07:5618,306-2
1 Nov 2026, 06:0018,308-2
31 Oct 2026, 03:2518,310+1
30 Oct 2026, 04:2718,309-2
29 Oct 2026, 03:3018,311+3
28 Oct 2026, 03:2718,308+8
25 Oct 2026, 23:4018,300-4
24 Oct 2026, 21:1718,304-4
23 Oct 2026, 18:5718,308-6
22 Oct 2026, 20:2818,314-8
21 Oct 2026, 13:0818,322+2
20 Oct 2026, 12:0118,320-4
18 Oct 2026, 16:1018,324-2
17 Oct 2026, 19:1018,326-3
16 Oct 2026, 19:5818,329first reading

Engagement

81 posts held, back to 23 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 73 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.40%
avg views ÷ 18,290 subscribers
Avg views / post
1,170
28 posts measured
Reaction rate
0.203%
reactions ÷ views · ER floor
Posts in window
28
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. It is computed over the 25 of 28 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 November 2026
Posts held81 (23 July 2026 – 10 November 2026)
Views total32,800
Reactions total62
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 04:19 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
≈2,820
Videos
≈167
Links
≈5,440

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. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
2m 48s
Average length
34s

Measured directly from 5 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

263 reactions across 65 posts, in 13 distinct kinds. The most used accounts for 43.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤11443.3%
👍8130.8%
😁228.37%
🔥217.98%
🥱51.90%
👏41.52%
👾41.52%
🙏31.14%
🤩31.14%
🎉20.76%
🥰20.76%
⚡10.38%
🌚10.38%

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 69 of the 81 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 290 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 81 most recent posts we hold, published 23 July 2026 to 10 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Advertising

Ad load
2.47%
2 of 81 posts carry an ad marker
Regulatory tokens
2
posts carrying an erid · 2 distinct tokens
Median views · ads
614
over 2 measured posts
Median views · rest
1,380
over 79 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
2SDnjcuT75V123 July 202623 July 2026
CQH36pWzJqVJCbWwdw8YPGbm54Rbkkq1PurWH8do19EkU612 September 20262 September 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 23 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: 0 of 28 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).

10 Nov 2026, 12:15 UTC541 viewsread 11 November 2026

🧠 Когда важный признак получает низкую importance У двух признаков сильная корреляция. При расчёте permutation importance перемешиваем один из них. Модель может по-прежнему получать похожую информацию из второго, и метрика почти не изменится. То же может произойти, если отдельно перемешать второй признак. Низкая importance каждого по отдельности ещё не означает, что вся группа бесполезна. Этот показатель описывает …

9 Nov 2026, 11:54 UTC797 viewsread 11 November 2026
Photo

Optuna: как сообщить pruner, что происходит с trial Sampler выбирает гиперпараметры, pruner решает, стоит ли досрочно остановить trial. Для решения ему нужны промежуточные значения метрики. Этот API предназначен для оптимизации одной целевой метрики. В цикле обучения вызывают trial.report(value, step), затем trial.should_prune(). Если ответ True, objective должен поднять optuna.TrialPruned(). Сам вызов report обуче…

8 Nov 2026, 12:01 UTC882 viewsread 11 November 2026
Photo

Запрос и документ: две роли в семантическом поиске В асимметричном поиске по короткому вопросу ищут более длинный абзац с ответом. Sentence Transformers рекомендует encode_query для запроса и encode_document для корпуса. Методы могут применять промпты и маршрутизацию, сохранённые в конкретной модели. Это не означает, что они всегда используют разные веса. Если модель не обучалась со специальными prompts или task t…

7 Nov 2026, 12:07 UTC890 views2 reactionsread 11 November 2026
Photo

Включите constrained layout до создания осей Если подписи осей и шкала colorbar не помещаются, попробуйте plt.subplots(layout="constrained"). Matplotlib перераспределит место между осями и подписями, сохраняя заданную сетку. Включать режим обычно нужно до добавления Axes. На изображении один и тот же синтетический массив, размер фигуры и шрифт. Сверху — стандартная компоновка с обрезанной подписью. Снизу — constrai…

👍1🤩1

6 Nov 2026, 11:46 UTC≈1,000 views1 reactionsread 11 November 2026
Photo

MLflow: что меняется при переназначении alias Alias champion в Model Registry можно переназначить с одной версии на другую. При загрузке URI вида models:/fraud@champion MLflow берёт версию, на которую alias указывает в этот момент. Имя fraud здесь условное. После переназначения следующий вызов load_model по этому URI загрузит новую версию. Уже загруженный Python-объект сам от этого не обновится. Для воспроизводимо…

👍1

5 Nov 2026, 11:57 UTC≈1,040 views2 reactionsread 11 November 2026
Photo

В парном bootstrap выбирайте строки целиком Если x и y относятся к одному наблюдению, при пересэмплировании нужно сохранить их пару. Например, для корреляции двух измерений у одних и тех же объектов. В scipy.stats.bootstrap параметр paired=True выбирает один массив индексов и применяет его ко всем входным массивам. При paired=False каждый массив пересэмплируется независимо. На схеме видно, какие пары сохраняет общи…

❤2

4 Nov 2026, 11:41 UTC≈1,080 views1 reactionsread 11 November 2026
Photo

Почему True | NA даёт True У nullable boolean в pandas три значения: True, False и NA. Результат будет NA, только если его нельзя определить по известному операнду. Поэтому True | NA даёт True, а True & NA — NA. На карточке — четыре сочетания для dtype="boolean". У фильтрации другое правило: NA в булевой маске исключает строку. Для данных [10, 20, 30] маска [True, False, NA] оставит [10]. Если нужно сохранить и стр…

👍1

3 Nov 2026, 11:59 UTC≈1,110 views5 reactionsread 11 November 2026
Photo

Куда HistGradientBoosting направляет строки с NaN В HistGradientBoostingClassifier пропуски можно оставить как NaN. При обучении дерево в каждом разбиении выбирает для них левую или правую ветвь по выигрышу от разбиения. При предсказании использует выученное направление. Есть отдельный случай: в обучении у этого признака пропусков не было, а при предсказании появился NaN. Тогда строка уйдёт в дочерний узел с больши…

❤4👍1

2 Nov 2026, 11:48 UTC≈1,190 views4 reactionsread 11 November 2026
Photo

📊 Расстояние между распределениями в понятных единицах В SciPy wasserstein_distance([0, 1, 3], [5, 6, 8]) возвращает 5,0. Второй набор сдвинут на пять единиц. На схеме каждая из трёх масс переносится на это расстояние. Wasserstein-1 — минимальная стоимость переноса вероятностной массы: масса × расстояние. Для одномерных распределений это также площадь между CDF. Аргументы функции — наблюдения или значения поддержк…

👍3❤1

1 Nov 2026, 11:52 UTC≈1,160 views3 reactionsread 11 November 2026
Photo

📊 Выделить область и подсветить точки в Altair На scatter plot хочется быстро рассмотреть часть объектов. В Altair прямоугольное выделение задаётся через alt.selection_interval() и подключается с add_params(brush). В официальном примере условие alt.when(brush) сохраняет цвет по числу цилиндров внутри выделения, а остальные точки делает серыми. Это изменение цвета, а не фильтрация данных. На нашей статичной схеме с…

❤2👍1

31 Oct 2026, 11:45 UTC≈1,180 views2 reactionsread 11 November 2026
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📊 STL: почему period=12, а seasonal=13 Для месячного ряда с годовым циклом period=12 означает 12 наблюдений в сезоне. А seasonal=13 задаёт нечётную длину окна сезонного сглаживания. Это разные параметры. STL с помощью LOESS раскладывает ряд на тренд, сезонность и остаток. На графике показана декомпозиция синтетического месячного ряда с этими настройками. robust=True уменьшает влияние больших ошибок через веса при …

⚡1❤1

30 Oct 2026, 14:28 UTC≈1,060 views2 reactionsread 11 November 2026
Photo

🔔 Последние дни акции Proglib Academy! Покупаете один курс — второй получаете в подарок. Успейте до 31 октября. Можно совместить два направления и прокачать навыки сразу в нескольких областях: ⬆️ ИИ для разработчиков — системная работа с ИИ на всех этапах разработки: от планирования задачи до написания кода, тестирования и ревью. ⬆️ Разработка ИИ-агентов — создание собственных агентов для работы с данными, API и в…

❤1🔥1

Showing the 12 most recent of 81 posts we hold for @dsproglib. 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 1 post on @dsproglib 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
19 August 2026
Most recent seen missing
19 August 2026
Median time before seen missing
35 hours
Seen missing in the last 30 days
0

Polls

The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.

2 Aug 2026, 16:54 UTCAnonymous Quiz300 voters

Что выведет код?

  1. 31525%
  2. 1616%
  3. Error57%
  4. 83%

Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.

Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.

The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.

Read from the 81 most recent posts we hold, published 23 July 2026 to 10 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.

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 6 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.

Библиотека питониста | Python, Django, Flask
@pyproglib · 36,972
Telegram ranks this channel #2 of 84 here — alongside 83 others — read 1 September 2026
hahacker_news
@hahacker_news · 25,231
Telegram ranks this channel #7 of 59 here — alongside 58 others — read 14 September 2026
Data Science | Machinelearning [ru]
@devsp · 19,659
Telegram ranks this channel #8 of 91 here — alongside 90 others — read 30 September 2026
Библиотека программиста
@proglibrary · 77,612
Telegram ranks this channel #12 of 82 here — alongside 81 others — read 19 August 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,923
Telegram ranks this channel #15 of 93 here — alongside 92 others — read 25 August 2026
Data Science
@datascienceiot · 42,496
Telegram ranks this channel #19 of 76 here — alongside 75 others — read 29 August 2026
Data Science Jobs
@datasciencejobs · 22,587
Telegram ranks this channel #21 of 93 here — alongside 92 others — read 21 September 2026
Python Books. Книги по питону
@pythonbooks · 38,331
Telegram ranks this channel #24 of 65 here — alongside 64 others — read 17 September 2026
Data Science Jobs
@datascienceml_jobs · 21,642
Telegram ranks this channel #27 of 97 here — alongside 96 others — read 24 September 2026
Physics.Math.Code
@physics_lib · 146,676
Telegram ranks this channel #27 of 72 here — alongside 71 others — read 13 August 2026
Data Science. SQL hub
@sqlhub · 36,025
Telegram ranks this channel #28 of 87 here — alongside 86 others — read 2 September 2026
Machine learning Interview
@machinelearning_interview · 30,560
Telegram ranks this channel #29 of 98 here — alongside 97 others — read 7 September 2026
Python вопросы с собеседований
@python_job_interview · 24,906
Telegram ranks this channel #33 of 90 here — alongside 89 others — read 15 September 2026
BZD • Книги для программистов
@bzd_channel · 36,213
Telegram ranks this channel #34 of 57 here — alongside 56 others — read 1 September 2026
Machinelearning
@ai_machinelearning_big_data · 275,659
Telegram ranks this channel #34 of 95 here — alongside 94 others — read 10 August 2026
Stepik – онлайн-курсы
@stepik_courses · 28,865
Telegram ranks this channel #36 of 93 here — alongside 92 others — read 16 September 2026
Zen of Python
@zen_of_python · 18,645
Telegram ranks this channel #38 of 91 here — alongside 90 others — read 5 October 2026
Pythonist.ru - образование по питону
@pythonist_ru · 23,873
Telegram ranks this channel #40 of 82 here — alongside 81 others — read 17 September 2026
NOP::Nuances of Programming
@nuancesprog · 55,956
Telegram ranks this channel #42 of 84 here — alongside 83 others — read 23 August 2026
Библиотека фронтендера | Frontend, JS, JavaScript, React.js, Angular.js, Vue.js
@frontendproglib · 20,611
Telegram ranks this channel #43 of 93 here — alongside 92 others — read 25 September 2026
Библиотека джависта | Java, Spring, Maven, Hibernate
@javaproglib · 21,787
Telegram ranks this channel #44 of 88 here — alongside 87 others — read 21 September 2026
Искусственный интеллект. Высокие технологии
@vistehno · 70,139
Telegram ranks this channel #46 of 94 here — alongside 93 others — read 20 August 2026
Python/ django
@pythonl · 58,287
Telegram ranks this channel #50 of 84 here — alongside 83 others — read 22 August 2026
Библиотека Go-разработчика | Golang
@goproglib · 23,896
Telegram ranks this channel #51 of 91 here — alongside 90 others — read 17 September 2026

This channel appears in 27 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 9 November 2026 — this entry's latest reading, not the date you are reading this.

“Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение” (@dsproglib), 18,290 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/dsproglib.

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.