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Channel

دیتایاد | هوش مصنوعی و علم داده

@datayad

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

5,940subscribers

+500 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1001535008204
TypeChannel
Username@datayad
CreatedBetween 1 August 2021 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live11 November 2026
Measurements held27
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/datayad

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 96% 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

5,4355,9405,687.56 August 2026 — 5,440 subscribers7 August 2026 — 5,437 subscribers10 August 2026 — 5,435 subscribers14 August 2026 — 5,493 subscribers17 August 2026 — 5,524 subscribers20 August 2026 — 5,522 subscribers24 August 2026 — 5,523 subscribers27 August 2026 — 5,597 subscribers30 August 2026 — 5,632 subscribers1 September 2026 — 5,649 subscribers5 September 2026 — 5,667 subscribers10 September 2026 — 5,672 subscribers14 September 2026 — 5,665 subscribers18 September 2026 — 5,663 subscribers26 September 2026 — 5,644 subscribers5 October 2026 — 5,631 subscribers11 October 2026 — 5,622 subscribers15 October 2026 — 5,618 subscribers18 October 2026 — 5,613 subscribers20 October 2026 — 5,733 subscribers23 October 2026 — 5,746 subscribers26 October 2026 — 5,741 subscribers29 October 2026 — 5,854 subscribers1 November 2026 — 5,903 subscribers4 November 2026 — 5,924 subscribers7 November 2026 — 5,939 subscribers11 November 2026 — 5,940 subscribers6 August 202611 November 2026
27 measurements spanning 96 days, net +500. 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 5,359–6,016 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)SubscribersChange
11 Nov 2026, 00:465,940+1
7 Nov 2026, 15:595,939+15
4 Nov 2026, 11:585,924+21
1 Nov 2026, 22:265,903+49
29 Oct 2026, 13:595,854+113
26 Oct 2026, 12:365,741-5
23 Oct 2026, 10:415,746+13
20 Oct 2026, 17:485,733+120
18 Oct 2026, 03:575,613-5
15 Oct 2026, 01:475,618-4
11 Oct 2026, 20:545,622-9
5 Oct 2026, 04:215,631-13
26 Sept 2026, 19:175,644-19
18 Sept 2026, 01:375,663-2
14 Sept 2026, 03:555,665-7
10 Sept 2026, 20:205,672+5
5 Sept 2026, 10:205,667+18
1 Sept 2026, 23:545,649+17
30 Aug 2026, 09:545,632+35
27 Aug 2026, 00:045,597first reading

Engagement

56 posts held, back to 30 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 10 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
17.2%
avg views ÷ 5,940 subscribers
Avg views / post
1,020
18 posts measured
Reaction rate
0.48%
reactions ÷ views · ER floor
Posts in window
18
of 56 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 15 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 1 November 2026
Posts held56 (30 July 2026 – 1 November 2026)
Views total18,352
Reactions total73
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken5 Nov 2026, 01:37 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

201 reactions across 42 posts, in 7 distinct kinds. The most used accounts for 56.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤11456.7%
🔥3115.4%
😍199.45%
👍188.96%
👏125.97%
🤯41.99%
🗿31.49%

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 42 of the 56 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 201 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 56 most recent posts we hold, published 30 July 2026 to 1 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 18 posts held from the last 30 days (11.1%) 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).

1 Nov 2026, 14:25 UTC547 views4 reactionsread 5 November 2026

🧠 توکنایزرها (Tokenizers)؛ چرا هوش مصنوعی برای فارسی‌زبان‌ها گرون‌تر تموم می‌شه؟ مدل‌های زبانی کلمات رو مثل ما نمی‌خونن؛ اونا متن رو به تیکه‌های کوچکی به اسم «توکن» خرد می‌کنن. اما برای زبان فارسی کار کمی گره می‌خوره. چون این مدل‌ها بیشتر روی دیتای انگلیسی آموزش دیدن، یه کلمه انگلیسی معمولاً یک توکن حساب می‌شه. اما همون معنی تو فارسی ممکنه به ۳ یا ۴ توکن بی‌معنی شکسته بشه. نتیجه این تیکه‌پاره شدن چیه؟ ✅ هزینه بیشت…

❤4

31 Oct 2026, 12:49 UTC680 views7 reactionsread 5 November 2026
File

📚 ۸ مقاله انقلابی تاریخ هوش مصنوعی اگه می‌خوای عمیق‌تر با تاریخچه و پیشرفت هوش مصنوعی آشنا بشی، این ۸ مقاله می‌تونن نقطه شروع خوبی باشن. از معرفی معماری ترنسفورمر (Transformer) و پیشرفت یادگیری عمیق تا مدل‌های زبانی بزرگ و مدل‌های تولید تصویر، هر کدوم از این پژوهش‌ها نقش مهمی در شکل‌گیری AI مدرن داشتن. 📑 فهرست مقاله‌ها: 1️⃣ Attention Is All You Need (2017) 2️⃣ ImageNet Classification with Deep Convolutional Neural …

😍3❤2👏1🤯1

30 Oct 2026, 13:28 UTC715 views2 reactionsread 5 November 2026
Photo

🚀 گوگل از Gemini 4 Carbon رونمایی کرد؛ مدلی برای برنامه‌نویسی پیچیده و امنیت سایبری! گوگل مدل جدید Gemini 4 Carbon رو معرفی کرده؛ مدلی که برای حل مسائل پیچیده برنامه‌نویسی، پیدا کردن باگ در کدبیس‌های بزرگ و اجرای وظایف چندمرحله‌ای طراحی شده. 📊 طبق گزارش گوگل، این مدل در بنچمارک‌های امنیت سایبری عملکرد قابل‌توجهی داشته و در شناسایی و اصلاح آسیب‌پذیری‌های نرم‌افزاری بهبود پیدا کرده. همچنین، در ارزیابی Artificial Anal…

❤2

29 Oct 2026, 14:28 UTC756 views3 reactionsread 5 November 2026
Photo

🧠 فراموشی فاجعه‌بار (Catastrophic Forgetting)؛ چرا مدل‌ها چیزای قبلی رو یادشون می‌ره؟ وقتی یه مدل زبانی رو روی یه دیتای جدید فاین‌تیون می‌کنیم، انتظار داریم مهارت‌های قبلیش رو هم حفظ کنه. اما داستان اینجاست که گاهی مدل به جای یادگیری مهارت جدید، اطلاعات قبلی رو کاملاً فراموش می‌کنه! تو شبکه‌های عصبی، یادگیری یعنی تغییر دادن وزن‌ها (Weights). وقتی این وزن‌ها رو برای داده‌های جدید به‌روز می‌کنیم، تنظیماتی که برای درک…

❤2🔥1

28 Oct 2026, 14:50 UTC819 viewsread 5 November 2026
Photo

📊 پولارس (Polars)؛ سرعت بیشتر در پردازش داده با موتور Rust سال‌هاست پانداس (Pandas) ابزار اصلی کار با دیتا تو پایتونه؛ اما ممکنه با دیتاهای حجیم کُند بشع و رم رو هم پر کنه. اینجاست که پولارس با موتور Rust میاد وسط. پولارس از همه هسته‌های پردازنده استفاده می‌کنه و با قابلیت Lazy Evaluation، محاسبات رو قبل از اجرا بهینه می‌کنه. مزیت‌های اصلیش 🚀 ✅ پردازش موازی و چندثردی ✅ بهینه‌سازی هوشمند کوئری‌ها ✅ مدیریت بهینه حاف…

27 Oct 2026, 16:16 UTC968 views9 reactionsread 5 November 2026

🧠 کنترل توهم (Hallucination)؛ چطور جلوی خیال‌پردازی مدل‌های زبانی رو بگیریم؟ وقتی یه مدل زبانی بزرگ (LLM) با اعتمادبه‌نفس کامل اطلاعات غلط می‌سازه، در واقع داره بر اساس احتمال کلمات بعدی حدس می‌زنه، نه اینکه حقیقت رو بدونه. اما تو پروژه‌های واقعی چطور می‌شه جلوی این خطاها رو گرفت؟ اینجا ۵ راهکار اصلی رو داریم: 🔹 1️⃣ استفاده از RAG (بازیابی و تولید تقویت‌شده) به‌جای تکیه بر حافظه داخلی، داکیومنت‌ها و دیتابیس‌های مع…

❤6👍3

26 Oct 2026, 13:27 UTC≈1,590 views13 reactionsread 5 November 2026
File

❌ همیشه احتمال قطع شدن دسترسی‌ها یا محدودیت‌های ناگهانی وجود داره. ✅ با اینکه باید امیدوار باشیم که این شرایط مجدد پیش نیاد اما داشتن یه راه‌حل جایگزین برای یادگیری واجبه! در این فایل ۸ تا کتاب عالی و مرجع در حوزه علم داده و هوش مصنوعی رو برای شما آماده کرده‌ایم که شامل این عناوین هست: 🔴 پایه و اساس ریاضی 1- Mathematics for Machine Learning 🟠 آمار و تحلیل داده 2- Practical Statistics for Data Scientists 3- Fundam…

🔥9❤2😍2

25 Oct 2026, 19:02 UTC≈1,160 viewsread 5 November 2026
Photo

💥دوره جامع نخبگان پایتون: 🔥شرایط پرداخت اقساط + تخفیف این یه دوره جامع و یک جعبه ابزار کامل برای علاقه مندان به برنامه نویسی پایتونه. 🎯 از مفاهیم پایه شروع شده و تا مهارت‌های پیشرفته برنامه‌نویسی و توسعه نرم افزار رو پوشش میده. 📚در واقع ۵ تا دوره در کنار هم این دوره جامع رو تشکیل دادن: ✅ دوره صفرتاصد پایتون ✅ آموزش رابط گرافیکی PyQt6 ✅ آموزش دیتابیس SQL ✅ مقدمات پایتون در علم داده ✅ آموزش Git 1️⃣ تو بخش اول از ابت…

24 Oct 2026, 09:39 UTC≈1,230 views2 reactionsread 5 November 2026

🤖 بهترین مدل‌های هوش مصنوعی برای اجرای روی کامپیوتر شخصی! در شرایط فعلی اینترنت برای استفاده از هوش مصنوعی، بهتره یه گزینه جایگزین داشته باشی. مدل‌های قدرتمندی وجود دارن که می‌تونی روی سیستم خودت اجراشون کنی؛ از چت و تحلیل تصویر گرفته تا برنامه‌نویسی و استدلال. 🔥 اما کدوم مدل برای سخت‌افزار تو مناسبه؟ 🔹 ۸ گیگابایت RAM | شروع با مدل‌های سبک مناسب برای لپ‌تاپ‌ها و سیستم‌های اقتصادی - مدل Qwen3.5 2B — چت، پاسخ‌گویی…

👏2

22 Oct 2026, 14:27 UTC≈1,160 views4 reactionsread 5 November 2026

🧠 پدیده گمشده در میانه‌ متن (Lost in the Middle)؛ چرا AI جزئیات وسط متون طولانی رو فراموش می‌کنه؟ ⚡️ احتمالاً برای شما هم پیش اومده که یه فایل یا مستند سنگین را بدید دست هوش مصنوعی و ازش بخواید یه اطلاعات خاص رو از دلش بیرون بکشه، اما مدل دقیقاً همون بخش وسطی رو کاملاً فراموش کنه! با اینکه این روزها مدل‌ها از پنجره‌های زمینه (Context Window) چند صد هزار توکنی و میلیونی پشتیبانی می‌کنن، اما این مشکل همچنان پابرجا س…

🔥3❤1

21 Oct 2026, 12:23 UTC≈1,050 views4 reactionsread 5 November 2026
Photo

🧠 مدل تصمیم‌گیری با مدل زبانی چه فرقی داره؟ مدل زبانی معمولی متن تولید می‌کنه؛ اما Decision Model برای انتخاب بین چند گزینه مشخص ساخته شده. به‌جای نوشتن جواب، مثلاً تشخیص می‌ده پیام کاربر باید به پشتیبانی بره یا فروش. ورودی رو می‌گیره و به گزینه‌های ممکن امتیاز یا احتمال می‌ده. 🔹 Routing: انتخاب مدل یا ابزار مناسب 🔹 Classification: دسته‌بندی پیام‌ها 🔹 Verification: بررسی خروجی یک مدل دیگر برای کارهایی که فقط به ی…

🔥4

20 Oct 2026, 10:51 UTC≈1,050 views2 reactionsread 5 November 2026

🚀 مینی‌مکس از مدل جدید M3.1 Flash رونمایی کرد؛ ارزون‌تر، سریع‌تر و با کانتکست ویندو ۱ میلیون توکنی شرکت مینی‌مکس از مدل چندوجهی جدیدش با نام M3.1 Flash رونمایی کرد؛ مدلی که با معماری MoE و ۴۲۸ میلیارد پارامتر کل (حدود ۲۳ میلیارد پارامتر فعال) توسعه پیدا کرده و روی کاغذ حرف‌های زیادی برای گفتن داره. اما داستان جالب‌تر اینجاست که این مدل توی ماه‌های گذشته تحت عنوان یک پروژه ناشناس با نام رمز «Space Bunny» تست می‌شده …

🔥1🤯1

Showing the 12 most recent of 56 posts we hold for @datayad. 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

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 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.

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.

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.

اطلاع‌رسانی کلاس‌ شیمی دکتر هادیان‌فرد
@hadianfard_class · 63,572
Telegram ranks this channel #19 of 70 here — alongside 69 others — read 22 August 2026
آهنگ های ترکیه ای
@turkishmusic2021 · 33,520
Telegram ranks this channel #54 of 64 here — alongside 63 others — read 4 September 2026
برنامه نویسی پایتون | هوش مصنوعی | دیتاساینس
@persianovin_channel · 19,199
Telegram ranks this channel #63 of 90 here — alongside 89 others — read 4 October 2026

This channel appears in 3 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 11 November 2026 — this entry's latest reading, not the date you are reading this.

“دیتایاد | هوش مصنوعی و علم داده” (@datayad), 5,940 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/datayad.

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.