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Channel

Задачи DS - Собеседования, Соревнования, ШАД

@zadachi_ds

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

8,415subscribers

+337 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001928114627
TypeChannel
Username@zadachi_ds
DescriptionЧат: @zadachi_ds_chat По всем вопросам: @vice22821
CreatedBetween 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 November 2026
Measurements held27
Confirmed unchanged1 time, most recently 13 November 2026
On Telegramt.me/zadachi_ds

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 12 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 3 other registered channels. This entry also sits inside a group of 6 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@algoses/58428 Jul 2026, 13:05 UTC@zadachi_ds/375 · this entry28 Jul 2026, 13:35 UTC1.0029 minutes
@algoses/5892 Aug 2026, 12:03 UTC@zadachi_ds/385 · this entry2 Aug 2026, 16:02 UTC1.004.0 hours
@algoses/5948 Aug 2026, 14:04 UTC@zadachi_ds/390 · this entry8 Aug 2026, 16:00 UTC1.001.9 hours
@algoses/59912 Aug 2026, 10:47 UTC@zadachi_ds/396 · this entry12 Aug 2026, 10:47 UTC1.00under a minute
@postypashki_old/18358 Aug 2026, 09:13 UTC@zadachi_ds/390 · this entry8 Aug 2026, 16:00 UTC1.006.8 hours
@postypashki_old/198018 Oct 2026, 17:06 UTC@zadachi_ds/460 · this entry18 Oct 2026, 20:23 UTC1.003.3 hours
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@algoses9 (8/8 hand-verifiable sample passed)1.0044 minutes@algoses (7–2)
@postypashki_old8 (8/8 hand-verifiable sample passed)1.007.0 hours@postypashki_old (7–1)
@chad_protocol5 (5/5 hand-verifiable sample passed)1.001.8 hours@chad_protocol (4–1)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 8 of the 9 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 50 comparable posts for this entry, running 13 June 2026 to 14 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 6 channels, the one whose matching posts we hold earliest is @ProdAnalysis. That channel is not among the channels listed above, so this entry may share no posts with it and this does not say where this entry’s content came from. It is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, last confirmed 15 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Channels linked by matching posts

This channel is in a group of 6 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

8,0788,4158,246.57 August 2026 — 8,078 subscribers7 August 2026 — 8,078 subscribers10 August 2026 — 8,094 subscribers13 August 2026 — 8,092 subscribers16 August 2026 — 8,095 subscribers19 August 2026 — 8,091 subscribers23 August 2026 — 8,106 subscribers25 August 2026 — 8,125 subscribers29 August 2026 — 8,138 subscribers1 September 2026 — 8,140 subscribers5 September 2026 — 8,153 subscribers10 September 2026 — 8,189 subscribers14 September 2026 — 8,209 subscribers17 September 2026 — 8,232 subscribers27 September 2026 — 8,266 subscribers5 October 2026 — 8,284 subscribers12 October 2026 — 8,294 subscribers15 October 2026 — 8,301 subscribers18 October 2026 — 8,310 subscribers21 October 2026 — 8,360 subscribers25 October 2026 — 8,371 subscribers28 October 2026 — 8,392 subscribers31 October 2026 — 8,395 subscribers3 November 2026 — 8,400 subscribers5 November 2026 — 8,406 subscribers8 November 2026 — 8,403 subscribers13 November 2026 — 8,415 subscribers7 August 202613 November 2026
27 measurements spanning 98 days, net +337. 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 8,027–8,466 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)SubscribersChange
13 Nov 2026, 10:598,415+12
8 Nov 2026, 22:398,403-3
5 Nov 2026, 22:178,406+6
3 Nov 2026, 01:358,400+5
31 Oct 2026, 01:298,395+3
28 Oct 2026, 08:178,392+21
25 Oct 2026, 00:368,371+11
21 Oct 2026, 17:378,360+50
18 Oct 2026, 07:448,310+9
15 Oct 2026, 08:078,301+7
12 Oct 2026, 07:388,294+10
5 Oct 2026, 07:388,284+18
27 Sept 2026, 05:198,266+34
17 Sept 2026, 23:018,232+23
14 Sept 2026, 05:578,209+20
10 Sept 2026, 05:378,189+36
5 Sept 2026, 04:558,153+13
1 Sept 2026, 04:468,140+2
29 Aug 2026, 05:368,138+13
25 Aug 2026, 19:428,125first reading

Engagement

55 posts held, back to 13 June 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 50 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
32.7%
avg views ÷ 8,415 subscribers
Avg views / post
2,750
18 posts measured
Reaction rate
0.358%
reactions ÷ views · ER floor
Posts in window
18
of 55 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 16 of 18 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 15 November 2026
Posts held55 (13 June 2026 – 15 November 2026)
Views total49,483
Reactions total159
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Nov 2026, 15:56 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
70
Videos
2
Links
135

Lifetime counters from Telegram’s own channel header, read 15 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

548 reactions across 47 posts, in 20 distinct kinds. The most used accounts for 46.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤25746.9%
🔥14526.5%
🍌346.20%
👍336.02%
🫡213.83%
🤓162.92%
🌚112.01%
💘71.28%
💅50.912%
🍾30.547%
🎉30.547%
🐳30.547%
❤‍🔥20.365%
👨‍💻20.365%
🌭10.182%
🍓10.182%
👀10.182%
💋10.182%
🕊10.182%
🦄10.182%

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 49 of the 55 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 548 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 55 most recent posts we hold, published 13 June 2026 to 15 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.

Recent posts

Telegram’s own ‘edited’ marker: 3 of 18 posts held from the last 30 days (16.7%) 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).

15 Nov 2026, 13:57 UTC763 views3 reactionsread 15 November 2026

ML Breadth: технический собес для пиндосов В другом посте о research стажировках в MANGA+ обещал рассказать про эту зверюгу ML Breadth. Это самый популярный этап, который встречается абсолютно везде: от небольших стартапов до гигантов вроде MANGA. Причем неважно, метите вы на позицию стажера или стаффа. Простыми словами это просто технический собес типо названным умным словом. Чаще всего эту секцию ставят на ранних…

🔥2❤1

15 Nov 2026, 10:07 UTC≈1,100 views2 reactionsread 15 November 2026

Реально собеседование ML System Design От тим лида WildBerries. Cмотрим! Смотрим! https://www.youtube.com/watch?v=UfTekz0bhiw Именно такие мок собесы мы проводим на нашем курсе ML System Design. Это лишь малая часть того, чему мы учим. Если хотите научиться щелкать кейсы как орешки, вести диалог и защищать свои решения, то вам к нам. Сейчас действует хорошая скидка в честь черной пятницы! ➡️ Записаться

❤1🔥1

14 Nov 2026, 14:26 UTC≈1,770 views13 reactionsread 15 November 2026
Video message

Video message, posted without a caption

🍌10❤2🫡1

14 Nov 2026, 14:26 UTC≈1,880 views10 reactionsread 15 November 2026

Эти пет проекты должен сделать каждый DL специалист Без пет-проектов на финальном собеседовании делать нечего. Но никто не ждет от вас гениального проекта с развернутой инфраструктурой и Kubernetes. Для стажера и джуна достаточно реализовать бейзлайны и показать, что вы понимаете специфику конкретных задач. Мы уже делали подобные подборки для других специальностей. 1. Computer Vision: от матриц на NumPy до детектор…

❤5🔥3❤‍🔥1🍓1

13 Nov 2026, 16:32 UTC≈1,650 views3 reactionsread 15 November 2026
File

Протокол System Design в WildBerries Попросил нашего преподавателя Макара MLOps инженера команды рекомендаций WB составить гайд-протокол, по которому он сам проводит собеседования. Его комментарий далее. На собеседованиях кандидаты часто проваливаются не в самом понимании как устроена та или иная модель, а на секции системного дизайна, где за час нужно придумать систему целиком и никто заранее не говорит, что именн…

🔥3

13 Nov 2026, 12:34 UTC≈1,720 views0 reactionsread 15 November 2026
Photo

Чёрная пятница от Поступашек! Товарищи, хотите получить оффер в бигтех, перейти на более высокую позицию или увеличить зарплату? Мы открыли распродажу всех карьерных курсов Поступашек, которые помогут достичь этих целей — записывайся 📌 Скидки действуют только до 15 ноября включительно! Все курсы и актуальные цены можно посмотреть на сайте. 🔊Обращаем внимание на новую линейку курсов по ML System Design, A/B-тестам,…

12 Nov 2026, 17:07 UTC≈2,740 views13 reactionsread 15 November 2026

Год в DeepPavlov: чем живёт российская LLM-лаборатория Уже писали про перспективы и отбор в лабораторию в прошлом посте. На прошлой неделе поговорил с нашим выпускником, который год проработал в лаборатории DeepPavlov на Физтехе. Дальше его рассказ. Как я туда попал На третьем курсе я делал курсовую на RuBERT -на модели для русского языка от лаборатории DeepPavlov, и наткнулся на ошибку в документации библиотеки. Н…

❤12💋1

8 Nov 2026, 17:07 UTC≈2,910 views19 reactionsread 15 November 2026

Один день из жизни стажера-аналитика в Т-банке Выпускника прошлого потока курса по АВ тестам, не упусти свой шанс забрать разбор Т-банка и уже зимой получить заветный оффер. Серьезно, это один из самых простых способов вката сейчас: подал анкету, зарешал экзамен по разбору с курса, прошел собесы по слитым протоколам собесов. ➡️ Записаться на курс Мой рабочий день начинается с планирования. Первым делом я проверяю к…

🤓15❤2🍌2

7 Nov 2026, 18:07 UTC≈2,690 views6 reactionsread 15 November 2026

5 причин, почему нужно податься на стажировку в Т-Банк Т-Банк открыл донабор на стажировку до 8 ноября по аналитике. Задания контеста уже опубликованы здесь. Разборы уже выложены на нашем курсе по АВ тестам, там же выложен разбор буткемпа Авито. ➡️ Записаться Ниже обсудим, почему Т-Банк ежегодно становится сам желаемым местом для старта карьеры и за что так любят желтый банк. 1. Понятный отбор 🟦Главная задача — п…

❤4👍1🔥1

5 Nov 2026, 17:04 UTC≈3,260 views8 reactionsread 15 November 2026

Полный цикл отбора в Авито Успешная история выпускника наших курсов, который сейчас работает продуктовым аналитиком в Авито. Прямо сейчас идет отбор на буткемп Авито, дедлайн до 5 ноября. Онлайн-тестирование Недавннее нововведение этого года, заменяет технический скриннинг. Представляет из себя тест из 30-40 вопросов на внешней платформе. Скринить, переходить между вкладками, копипастить нельзя, но вебку не записыв…

❤8

2 Nov 2026, 16:07 UTC≈2,950 views2 reactionsread 15 November 2026

Как затащить ML/AI System Design (в WildBerries) От тим лида WildBerries. В эпоху, когда лайвкодинг отходит на второй план с развитием нейросетей, на первый план выходит понимание архитектуры. Чтобы вы не теряли офферы, мы разработали универсальную формулу решения таких кейсов на собесах и продемонстрировали ее на нескольких примерах. Смотрим! Смотрим! https://www.youtube.com/watch?v=ju1Qf6zoqfI Это лишь малая час…

❤1🔥1

1 Nov 2026, 18:08 UTC≈2,010 viewsread 15 November 2026
Forwarded from @postypashki_old

Почему ты не можешь найти работу Сейчас многие месяцами ищут работу, рассылают сотни откликов на hh и получают отказы или вообще тишину. При этом продолжают ботать SQL, Python, алгоритмы и готовиться к техническим собеседованиям, хотя проблема может быть совсем не в знаниях. Далеко не все понимают, как правильно искать работу, выходить на работодателей и показывать свою ценность среди других кандидатов. На одну вак…

Showing the 12 most recent of 55 posts we hold for @zadachi_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.

Posts recorded as deleted after publishing

We recorded 6 posts on @zadachi_ds 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
20 August 2026
Most recent seen missing
14 November 2026
Median time before seen missing
5 days
Seen missing in the last 30 days
2

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 1 registered channel — 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.

Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 47,236
Telegram ranks this channel #9 of 90 here — alongside 89 others — read 28 August 2026
Т-Образование
@tbank_education · 113,733
Telegram ranks this channel #33 of 91 here — alongside 90 others — read 14 August 2026
Young&&Yandex
@Young_and_Yandex · 112,971
Telegram ranks this channel #40 of 92 here — alongside 91 others — read 14 August 2026
Яндекс Образование
@Education_Yandex · 38,125
Telegram ranks this channel #58 of 96 here — alongside 95 others — read 31 August 2026

This channel appears in 4 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 13 November 2026 — this entry's latest reading, not the date you are reading this.

“Задачи DS - Собеседования, Соревнования, ШАД” (@zadachi_ds), 8,415 subscribers as measured 13 November 2026. Telegram Register, tgregister.com/channel/zadachi_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.