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 11 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.
Growth
54 measurements spanning 90 days, net -128. 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 12,447–12,653 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 54
Measured (UTC)
Subscribers
Change
4 Nov 2026, 08:45
12,471
-11
3 Nov 2026, 06:27
12,482
-6
31 Oct 2026, 06:29
12,488
-4
30 Oct 2026, 08:57
12,492
-5
29 Oct 2026, 06:39
12,497
-8
28 Oct 2026, 05:50
12,505
+2
27 Oct 2026, 02:19
12,503
+1
25 Oct 2026, 02:07
12,502
-7
24 Oct 2026, 00:56
12,509
-3
23 Oct 2026, 04:29
12,512
+3
22 Oct 2026, 01:07
12,509
+5
20 Oct 2026, 21:01
12,504
+4
19 Oct 2026, 19:41
12,500
-7
18 Oct 2026, 19:00
12,507
-6
17 Oct 2026, 21:45
12,513
-4
16 Oct 2026, 18:10
12,517
+3
15 Oct 2026, 15:27
12,514
-3
14 Oct 2026, 13:37
12,517
+8
13 Oct 2026, 05:07
12,509
-10
8 Oct 2026, 19:40
12,519
first reading
Engagement
164 posts held, back to 2 August 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 49 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.23%
avg views ÷ 12,471 subscribers
Avg views / post
1,150
23 posts measured
Reaction rate
1.15%
reactions ÷ views · ER floor
Posts in window
23
of 164 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 21 of 23 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 3 November 2026
Posts held
164 (2 August 2026 – 3 November 2026)
Views total
26,464
Reactions total
289
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Nov 2026, 18:14 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.
What this channel posts
Video runtime
3m 50s
Average length
29s
Measured directly from 8 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
1,896 reactions across 150 posts, in 15 distinct kinds. The most used accounts for 35.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
664
35.0%
🤣
422
22.3%
👍
338
17.8%
💔
226
11.9%
❤🔥
60
3.16%
🔥
42
2.22%
👎
34
1.79%
🗿
29
1.53%
😍
23
1.21%
🍾
20
1.05%
🆒
15
0.791%
👏
10
0.527%
🏆
5
0.264%
👌
5
0.264%
🤝
3
0.158%
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 151 of the 164 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 1,896 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 164 most recent posts we hold, published 2 August 2026 to 3 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: 2 of 23 posts held from the last 30 days (8.70%) 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).
تا الان با Ollama میشد مدلهای AI رو روی سیستم خودت اجرا کنی.
حالا یه قابلیت خیلی جذاب بهش اضافه شده:
هوش مصنوعی لوکالت میتونه حرف هم بزنه!
ابزار Ollama پشتیبانی از تولید صدا رو با مدل Phonon شروع کرده.
یعنی میتونی یه مدل زبانی رو روی سیستم خودت اجرا کنی، جواب تولید کنه و همون جواب رو به صورت زنده تبدیل به صدا کنه؛ بدون اینکه مجبور باشی برای TTS بری سراغ یه سرویس Cloud جدا.
چرا جذابه؟
- مدلها از حدود 31M پا…
🖥 وبینار رایگان: آیا DevOps بدون دخالت انسان هم میتواند کار کند؟
🤖نگاهی عملی به ساخت AI Agent برای مدیریت و اتوماسیون زیرساخت با استفاده از مدلهای هوش مصنوعی اوپن سورس
🎙ارائه دهنده : علیرضا صدرایی راد
📅 تاریخ برگزاری: ۱۹ آبان ماه ۱۴۰۵
از ساعت ۱۹ الی ۲۱
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Abrh.ir/latestwebinar 🔗
👆👆👆
در کانال ابرها عضو شوید: ✌️
📣@abrhacom
انگاری تو اندروید 17 QPR1
دیگه برنامه ها نمیتونن developer options رو تشخیص بدن.
یادمه یه سری برنامه های ایرانی بانکی مخصوصا, نمیذاشتن باهاشون کار کنی و باید این آپشن بسته میشد.
یه قابلیت خفن از دنیای برنامهنویسی که احتمالاً خیلیها هنوز باهاش آشنا نیستن!
اسمش Remotion Lambda هست.
تصور کن بهجای اینکه ویدیوت رو روی یک سرور رندر کنی و چند دقیقه یا حتی چند ساعت منتظر بمونی، کار رو بین صدها ماشین تقسیم کنی تا همزمان انجامش بدن!
داستان چیه؟
با React و JavaScript ویدیو میسازی، بعد Remotion Lambda ویدیوت رو به قسمتهای کوچیک تقسیم میکنه و روی AWS Lambda بهصورت موازی رندر میگیره.
آخرش هم…
۵ منبع رایگان طراحی با AI که بهتره بوکمارک کنی
۱. GetLayers
مجموعهای از Promptهای طراحی سایت، پسزمینهها، بخشهای متحرک و گرادیانتها. میتونی Promptها رو کپی کنی و به Claude بدی تا طراحی موردنظرت رو پیادهسازی کنه.
https://getlayers.ai
۲. Land-book
گالری منتخب از طراحی سایتها و Landing Pageهای حرفهای برای پیدا کردن ایده و الهام گرفتن.
https://land-book.com
۳. Recent
گالری جذابی از نمونههای جدید طراحی وب، اپل…
🔴 وقتی یک صرافی هک میشه، پول ها چطور ناپدید میشن؟
📰شاید برات سوال باشه وقتی هکرها میلیاردها دلار از یک صرافی سرقت میکنن، چرا نمیشه به راحتی پول ها رو پیدا کرد و برگردوند؟
▫️ ️ماجرا اینه که در دنیای ارزهای دیجیتال، پول مثل اسکناس از یک دست به دست دیگه منتقل نمیشه؛ بلکه دارایی ها بین آدرس های کیف پول و شبکه های مختلف جابهجا میشن.
🔍 بعد از سرقت چه اتفاقی میفته؟
⬅️- تقسیم دارایی ها: مبالغ بزرگ به چندین بخش کوچکتر تق…
🔴 وقتی یک صرافی هک میشه، پول ها چطور ناپدید میشن؟
📰شاید برات سوال باشه وقتی هکرها میلیاردها دلار از یک صرافی سرقت میکنن، چرا نمیشه به راحتی پول ها رو پیدا کرد و برگردوند؟
▫️ ️ماجرا اینه که در دنیای ارزهای دیجیتال، پول مثل اسکناس از یک دست به دست دیگه منتقل نمیشه؛ بلکه دارایی ها بین آدرس های کیف پول و شبکه های مختلف جابهجا میشن.
🔍 بعد از سرقت چه اتفاقی میفته؟
⬅️- تقسیم دارایی ها: مبالغ بزرگ به چندین بخش کوچکتر تق…
💡 ترفند روز تایپاسکریپت: کلیدواژه satisfies چیست و چرا باید جایگزین Type Assertion شود؟
بسیاری از توسعهدهندگان هنگام تعریف اشیاء یا از as Type استفاده میکنند یا تایپ متغیر را صریح میگذارند. اما کلیدواژه satisfies تایپ شیء را با اینترفیس تطبیق داده بدون اینکه خروجی دقیق فیلدها را به تایپ عمومی تقلیل دهد:
const config = {
host: "localhost",
port: 8080,
} satisfies Record<string, string | number>;
// config.p…
🚀 مایکروسافت یه دوره رایگان برای یادگیری هوش مصنوعی منتشر کرد | زبان فارسی هم پشتیبانی میکنه!
▪️اگه میخوای از کار با ChatGPT فراتر بری و یاد بگیری چطور ابزارها و برنامه های هوشمند خودت رو بسازی، این دوره میتونه شروع خیلی خوبی باشه.
▪️دوره Generative AI for Beginners توسط تیم Microsoft Cloud Advocates تهیه شده و شامل ۲۱ درس آموزشی به همراه یک بخش مقدماتیه.
▫️مفاهیم هوش مصنوعی مولد و مدل های زبانی بزرگ
▫️اصول پرامپ…
🔹ماهواره هوش مصنوعی گوگل اولین پاسخ خود را از مدار به زمین فرستاد
🔹 گوگل موفق شد با فعالسازی پردازندههای گرافیکی و اختصاصی هوش مصنوعی خود در مدار زمین، نخستین پاسخ از ماهواره آزمایشی پروژه سانکچر را ثبت کند. در این آزمایش مدل زبانی Gemma 4 توانست به دستوری برای نوشتن یک شعر کوتاه درباره حضور خود در مدار پاسخ دهد و متن را به زمین مخابره کند.
🔹 این اقدام در چارچوب پروژه سانکچر با هدف استقرار سرورهای هوش مصنوعی در…
👏6❤2
Showing the 12 most recent of 164 posts we hold for @barnamenevisanesf. 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 edited after publishing
@barnamenevisanesf edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
22 August 2026
Most recent edit
22 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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 4 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.
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
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@barnamenevisanesf named 1 handle 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@canva named in 2 posts, 8 August 2026 – 9 August 2026
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.
Top Learn | تاپ لرن @top_learn · 19,325 Telegram ranks this channel #7 of 89 here — alongside 88 others — read 1 October 2026
هوش مصنوعی از صفر تا درآمد @mohsenmodhejaip · 45,775 Telegram ranks this channel #27 of 82 here — alongside 81 others — read 26 August 2026
Html and Css & Jsآموزش @htmlcss_channels · 22,686 Telegram ranks this channel #35 of 86 here — alongside 85 others — read 19 September 2026
آموزش برنامه نویسی و طراحی سایت - سورس ایران @sourceiran · 20,890 Telegram ranks this channel #36 of 82 here — alongside 81 others — read 24 September 2026
برنامه نویسی پایتون | هوش مصنوعی | دیتاساینس @persianovin_channel · 19,121 Telegram ranks this channel #42 of 90 here — alongside 89 others — read 4 October 2026
برنامه نویسی | Programming @hedcode · 19,512 Telegram ranks this channel #44 of 75 here — alongside 74 others — read 1 October 2026
Poyot Academy @poyotacademy · 27,029 Telegram ranks this channel #60 of 85 here — alongside 84 others — read 19 September 2026
This channel appears in 7 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 4 November 2026 — this
entry's latest reading, not the date you are reading this.
“کدیاد | Codeyad | آموزش برنامه نویسی” (@barnamenevisanesf), 12,471 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/barnamenevisanesf.
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.