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 15 September 2026 and assigned it the closest of 31 fixed categories, at 67% 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
15 measurements spanning 43 days, net -29. 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 2,888–2,940 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
18 Sept 2026, 17:55
2,902
-8
14 Sept 2026, 19:39
2,910
+8
11 Sept 2026, 14:59
2,902
+5
7 Sept 2026, 10:21
2,897
+1
2 Sept 2026, 08:04
2,896
-4
30 Aug 2026, 00:34
2,900
+6
26 Aug 2026, 19:39
2,894
-5
23 Aug 2026, 10:36
2,899
-8
19 Aug 2026, 19:41
2,907
-7
16 Aug 2026, 16:36
2,914
-4
12 Aug 2026, 22:23
2,918
-14
9 Aug 2026, 19:02
2,932
-2
7 Aug 2026, 04:45
2,934
+3
6 Aug 2026, 21:00
2,931
no change
6 Aug 2026, 20:49
2,931
first reading
Engagement
22 posts held, back to 21 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 3 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 22 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
29 reactions across 14 posts, in 6 distinct kinds. The most used accounts for 48.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
14
48.3%
👎
5
17.2%
👏
4
13.8%
🥰
3
10.3%
❤
2
6.90%
🔥
1
3.45%
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 15 of the 22 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 29 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 21 July 2026 to 7 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.
وبینار دیتا ساینس در دنیای واقعی 🐈⬛📊
از مدلهای یادگیری ماشین تا خلق محصولات دادهمحور 🧬 🧪
💡 فکر میکنید دیتا ساینس فقط ساخت مدلهای پیشبینی است؟
✅ در واقع، مدلها بهتنهایی ارزشی ایجاد نمیکنند؛ ارزش واقعی زمانی شکل میگیرد که به محصولات دادهمحور (Data Products) تبدیل شوند.
🎯 در این وبینار کوتاه میبینید:
🔴 یک Data Product چیست و چه تفاوتی با مدل Machine Learning دارد؟
🔴 شرکتها چگونه از #داده برای ساخت محصول…
🔹تخفیف تکرار نشدنی 🔹
⭕️کاملترین پکیج آموزش نقشه خوانی صنعتی⭕️
سلام خدمت همه عزیزان
مفتخریم تا کاملترین پکیج آموزش نقشه خوانی،ویژه دانشجویان ،صنعتگران و علاقه مندان مهندسی مکانیک را به شما معرفی کنیم.این محصول حاصل بیش از 15 سال تجربه صنعتی بوده که در یک مجموعه جمع آوری شده است.
برای مشاهده سرفصل کامل بر روی لینک زیر کلیک نمایید.
مشاهده سرفصل
نمونه ویدئو از پروژه های انجام شده
نمونه نقشه انجام شده ۱ شامل تعریف پ…
وبینار دیتا ساینس در دنیای واقعی 🐈⬛📊
از مدلهای یادگیری ماشین تا خلق محصولات دادهمحور 🧬 🧪
💡 فکر میکنید دیتا ساینس فقط ساخت مدلهای پیشبینی است؟
✅ در واقع، مدلها بهتنهایی ارزشی ایجاد نمیکنند؛ ارزش واقعی زمانی شکل میگیرد که به محصولات دادهمحور (Data Products) تبدیل شوند.
🎯 در این وبینار کوتاه میبینید:
🔴 یک Data Product چیست و چه تفاوتی با مدل Machine Learning دارد؟
🔴 شرکتها چگونه از #داده برای ساخت محصول…
Showing the 12 most recent of 22 posts we hold for @magic_gif. 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.
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 29 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
Named by
Channels on the register whose posts name this channel's handle.
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.
Handles this channel named that no longer answer
Dead references
2
handles named in this channel’s posts, vacant today
Evidenced gone
2
we ourselves saw one of these resolve, at some point
Never seen alive
0
vacant every time we have ever looked
@magic_gif named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@farsii_film named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 12 September 2026 (two independent sightings — see how we confirm a dead handle)evidenced
@poroje_vip named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 12 September 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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.
Production Line @ProductionLine · 25,715 Telegram ranks this channel #12 of 86 here — alongside 85 others — read 13 September 2026
How It's Made @How_It_Made · 26,946 Telegram ranks this channel #17 of 75 here — alongside 74 others — read 11 September 2026
Mekanism | مکانیزمها @mekanism · 57,254 Telegram ranks this channel #28 of 82 here — alongside 81 others — read 23 August 2026
love ♡ @LOVENEOWW · 37,748 Telegram ranks this channel #35 of 40 here — alongside 39 others — read 31 August 2026
Proxy Saver @Proxysarver · 31,783 Telegram ranks this channel #42 of 72 here — alongside 71 others — read 6 September 2026
کافه کتاب @CafeKetab · 57,941 Telegram ranks this channel #44 of 69 here — alongside 68 others — read 13 September 2026
📚University_books @UNIVERSITY_BOOKSS · 34,960 Telegram ranks this channel #64 of 79 here — alongside 78 others — read 3 September 2026
آموزش نرم افزار های مهندسی @mohandes_yar · 28,660 Telegram ranks this channel #77 of 87 here — alongside 86 others — read 9 September 2026
This channel appears in 8 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Magic_Gif” (@magic_gif), 2,902 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/magic_gif.
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.
