Channel
@datayad
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
5,435subscribers
-5 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001535008204 |
|---|---|
| Type | Channel |
| Username | @datayad |
| Description | 🔥 تخفیفات تابستونه دیتایاد شروع شد! دوره های جامع پایتون، علم داده و یادگیری ماشین و دیگر دوره های مرتبط با این حوزه (با بالا ترین سطح رضایت دانشجویان دوره) سایت دیتایاد: https://datayad.com پشتیبانی دیتایاد در بله: https://ble.ir/@datayad_support |
| Created | Between 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/datayad |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 23:02 | 5,435 | -2 |
| 7 Aug 2026, 21:33 | 5,437 | -3 |
| 6 Aug 2026, 23:32 | 5,440 | first reading |
36 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 8 pagesof Telegram’s post history, 20 posts per page.
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 36 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 11 August 2026 |
|---|---|
| Posts held | 36 (30 July 2026 – 11 August 2026) |
| Views total | 18,378 |
| Reactions total | 115 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 04:18 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.
Lifetime counters from Telegram’s own channel header, read 12 August 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.
115 reactions across 25 posts, in 6 distinct kinds. The most used accounts for 70.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 81 | 70.4% | |
| 😍 | 14 | 12.2% | |
| 👍 | 13 | 11.3% | |
| 🔥 | 3 | 2.61% | |
| 🗿 | 3 | 2.61% | |
| 👏 | 1 | 0.87% |
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 25 of the 36 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 115reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 36 most recent posts we hold, published 30 July 2026 to 11 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.
باید آموزش ببینید، کد بزنید، پروژه انجام بدید، روی دیتاستهای مختلف کار کنید، اشتباه کنید و دوباره تلاش کنید. دیتایاد قرار نیست رویا بفروشه؛ قرارِ واقعیت رو بهتون بگه. اگر واقعاً میخواید وارد AI بشید، باید برای یادگیری واقعی وقت بذارید. 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
👍2
دیتایاد قرار نیست بهتون بگه: «فقط یک ماه آموزش ببین و بعدش درآمد دلاری داشته باش!» ❌ این حرفها بیشتر برای فروش دوره خوبه تا یادگیری واقعی. ✅ یادگیری AI تلاش میخواد. 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
👍1
⁉️ پس اون ۳ برابر زمان اضافه کجا میره؟ 💻 بخشی از زمانت باید صرف کدنویسی با دست خودت بشه. کدهای آموزش رو خودت بنویس، تغییرشون بده، خرابشون کن و دوباره درستشون کن. بعدش هم برو سراغ Kaggle و دیتاستهای مشابه پیدا کن و همون چیزی که یاد گرفتی رو روی دادههای جدید پیاده کن. ✅ اینجاست که فاصلهی بین «فهمیدم» و «بلدم انجامش بدم» مشخص میشه. مهارت با دیدن ساخته نمیشه؛ با حل مسئله و تمرین ساخته میشه. 📌مرجع تخصصی هوش مص…
❤2👍1
⁉️ یادگیری AI چقدر طول میکشه؟ جوابش خیلی سادهست: ✅ به خودت بستگی داره! ⭕ ولی یه قانون تجربی خوب اینه که مدت زمان آموزش رو ضربدر ۴ کنی. مثلاً آموزش متخصص علم داده 100 ساعت ویدیو آموزشی داره، فکر نکن با 100 ساعت دیدنش مسلط میشی. حدود 400 ساعت زمان برای یادگیری و تمرین در نظر بگیر. حالا به خودت بستگی داره تو چندماه بتونی این 400 ساعت رو پر کنی! چرا؟ 👇 چون دیدن ویدیو فقط بخش کوچیکی از مسیر یادگیریه. 📌مرجع تخصصی…
❤2👍2
🔻 پس Muse Spark هکره؟ 🤖💻 نه دقیقاً! مدل برای انجام تستهای امنیتی آموزش/تنظیم شده بود و در این آزمایش هم قرار بوده دنبال آسیبپذیری بگرده. مشکل اینجا بود که بهجای یک محیط کاملاً ایزوله، به اینترنت واقعی دسترسی پیدا کرد. بعد هم از یک آسیبپذیری واقعی استفاده کرد. پس اتفاق مهمتر از «هوش هکری مدل» اینه: هرچه Agentها قدرتمندتر میشن، اشتباهات کوچک در مجوزها و محیط اجرا میتونن پیامدهای واقعی داشته باشن. این دقیقا…
🔻 فکتچک: مدل متا واقعاً یک شرکت را هک کرد؟ بله! 😐 مدل Muse Spark 1.1 متا در جریان یک تست امنیت سایبری، به اینترنت دسترسی پیدا کرد و بعد از سوءاستفاده از یک آسیبپذیری در سرویس شخص ثالث، وارد سیستم یک شرکت واقعی شد و تغییراتی در آن ایجاد کرد. اما این اشتباهه: ❌ مدل «سندباکس امن رو شکست و فرار کرد» ✅ محیط تست بهاشتباه طوری پیکربندی شده بود که مدل به اینترنت دسترسی داشت. ❌یعنی اصل هک واقعی بوده، ولی تیتر «فرار از…
پست های آموزشی مارو با #آموزشی دنبال کنید! 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
❤2
👍 این یکی از پایههای اصلی تکنولوژیهای جدید هوش مصنوعیه. از موتورهای جستجوی هوشمند و RAG گرفته تا مدلهای زبانی بزرگ مثل ChatGPT، همه به نوعی با Embedding کار میکنن. 📌 یکی از اولین قدم ها در آموزش LLM و NLP دیتایاد همین موضوعه 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
❤1👏1
مثلا در فضای Embedding، کلمات: 👨 شاه 👩 ملکه از نظر معنایی به هم نزدیک هستن. یا: 🐕 سگ 🐈 گربه به هم نزدیکن ولی از ماشین دورتر هستن. مدل با همین فاصلهها و ارتباطها میتونه مفهوم متن رو بهتر درک کنه. 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
❤1
✅ در واقع Embedding یعنی تبدیل کلمات، جملهها یا حتی تصاویر به یک مجموعه عددی که بهش میگیم Vector. ⭕ ما نکته جالب اینجاست: این عددها فقط کدگذاری ساده نیستن؛ اطلاعاتی درباره معنی و ارتباط بین مفاهیم داخلشون ذخیره میشه. 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
🧠 مفهوم Embedding چیه؟ کامپیوتر متن رو مثل ما نمیفهمه. برای اینکه یک مدل هوش مصنوعی بتونه با کلمات کار کنه، باید اونها رو به عدد تبدیل کنیم. اینجاست که Embedding وارد میشه. #آموزشی 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
✅ اگه یه سر به لیست سرفصل های آموزش متخصص علم داده بندازید، کامل متوجه میشید که بخش برنامه نویسی چند درصد از مطالب یک آموزش جامع رو به خودش اختصاص میده! 📌مرجع تخصصی هوش مصنوعی و علم داده ❇️ سایت | بله | تلگرام | اینستاگرام
Showing the 12 most recent of 36 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.
Citation-graph rank — 632,399 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
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.
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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“دیتایاد | هوش مصنوعی و علم داده” (@datayad), 5,435 subscribers as measured 10 August 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.