Channel
@class_vision
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
2,996subscribers
+102 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001292563085 |
|---|---|
| Type | Channel |
| Username | @class_vision |
| Created | Between 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/class_vision |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 21:57 | 2,996 | +88 |
| 9 Aug 2026, 20:32 | 2,908 | +11 |
| 6 Aug 2026, 16:30 | 2,897 | +3 |
| 6 Aug 2026, 05:04 | 2,894 | no change |
| 6 Aug 2026, 04:06 | 2,894 | first reading |
20 posts held, back to 18 November 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 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.
| Window | Rolling 30 days · latest post in window 31 July 2026 |
|---|---|
| Posts held | 20 (18 November 2025 – 31 July 2026) |
| Views total | 7,003 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 16:04 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.
Measured directly from 3 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.
🤖 دوره Agentic AI با پایتون — از LLM تا ساخت Agentهای واقعی در این دوره فقط با APIها کار نمیکنیم؛ Agentهایی میسازیم که میتوانند ابزار استفاده کنند، بازخورد بگیرند و وظایف پیچیده را انجام دهند. ⚙️ چیزهایی که واقعاً پیادهسازی میکنی: ▸ الگوی Reflection برای self-critique و بهبود خروجی (SQL، مقاله، تصویر و...) ▸ Tool Use از صفر — تبدیل توابع پایتون به Tool قابل فراخوانی توسط مدل ▸ ساخت MCP Server و MCP Client، و ا…
اگر کسی وب و کلاینت کار میکنه، این دوره را نیز به مدت محدود میتوانید رایگان ببینید: مینی دوره ساخت هوش مصنوعی شخصی در مرورگر COUPON-B7F7C
🔥 فرصت طلایی یادگیری هوش مصنوعی از امروز شروع میشه! اگه دنبال یه بهونه بودین که بالاخره وارد دنیای AI و LLM بشین، بهترین زمانشه ⚡️ به مناسبت انتشار دوره جدید، 70 درصد تخفیف روی همه دورههای #هوش_مصنوعی، #LLM و پردازش_تصویر آموزش هوش مصنوعی مولد با مدلهای زبانی بزرگ (LLM) https://mktb.me/04dr/ COUPON-D9D48 آموزش مدلهای زبانی-تصویری (VLM): از درک تصویر و ویدیو تا فاینتیون پیشرفته https://mktb.me/e3gx/ COUPON-A7E…
📢 اگر پست دیروز را ندیدید... دوره Agentic AI با پایتون منتشر شده و از مفاهیم پایه تا ساخت Agentهای حرفهای، MCP، Tool Use، سیستمهای چندعامله با crewAI، LangChain و پروژهی نهایی Text-to-SQL را بهصورت عملی آموزش میدهد. 🎁 هنوز کد تخفیف ۶۰٪ برای تعداد محدودی از ثبتنامها فعال است: COUPON-6EE77 https://mktb.me/m6tt/ اگر قصد یادگیری Agentic AI را دارید، پیشنهاد میکنم فرصت باقیمانده را از دست ندهید. 📚 سرفصلها،…
🎁 تخفیف ویژه 1️⃣برای ۱۰۰ نفر اول، کد تخفیف ۷۰٪ی: COUPON-EAA61 2️⃣ برای ۱۰۰ نفر بعدی، کد تخفیف ۶۰٪ی: COUPON-6EE77 https://mktb.me/m6tt/
🤖 دوره «Agentic AI با پایتون» منتشر شد! اگه دنبال این هستی که از حرف زدن با یه مدل زبانی، بری سراغ ساختن عاملهایی (Agent) که واقعاً کار انجام میدن، ابزار صدا میزنن، با هم تیم میشن و پروژههای واقعی رو پیش میبرن، این دوره برای شماست! توی ۸ فصل، از صفر تا ساخت یک پروژهی نهایی کامل جلو میریم: 📘 مقدمه 📗 فصل ۱ - مقدمهای بر گردشکارهای عاملمحور 📗 فصل ۲ - الگوی طراحی Reflection 📗 فصل ۳ - استفاده از ابزار (Tool U…
تخفیف ویژه تابستانی روی دوره یادگیری عمیق: https://class.vision/product/%d8%af%d9%88%d8%b1%d9%87-%d8%ac%d8%a7%d9%85%d8%b9-deeplearning/
تمام ویدویهای دوره RNN-LSTM_GRU که چندماه پیش رایگان شده بود در لیست پخش آپارات نیز قرار داده شد https://www.aparat.com/playlist/287685/
منتظر انتشار دوره Agentic AI باشید... این دوره در 8 فصل ضبط شده است 🔹 Reflection 🔹 Tool Use 🔹 Planning 🔹 Multi-Agent Collaboration 🔹 Model Context Protocol (MCP) 🔹 Evaluation of Agentic Systems 🔹 CrewAI Framework 🔹 LangChain
سلام و درود خدمت دوستان و همراهان گرامی 🌱 با توجه به پیامهایی که اخیراً دریافت کردهام، لازم دانستم توضیح کوتاهی ارائه کنم. در حال حاضر بنده در هیچ مؤسسهای (چه بهصورت حضوری و چه آنلاین) که ثبتنام دورهای در این فصل داشته باشد، تدریس نمیکنم. برخی از مواردی که نام بنده در معرفی دورهها یا صفحات مؤسسات درج شده، مربوط به همکاریهای قبلی بوده است. همچنین چند موردی که دوستان ارسال کردهاند و دورهای با عنوان مدرس «…
📢🎉کد تخفیف ویژه اعضای محترم کانال به مناسبت عید غدیر کد تخفیف 800 هزارتومانی شبکه های عصبی گرافی gnn_ghadir_1405 کد تخفیف 60 درصدی آموزش هوش مصنوعی مولد با مدلهای زبانی بزرگ (LLM) COUPON-A7EDE کد 70 درصد تخفیف آموزش مدلهای زبانی-تصویری (VLM): از درک تصویر و ویدیو تا فاینتیون پیشرفته COUPON-DDAEC کد تخفیف 70 درصدی آموزش جامع یادگیری عمیق(Deep Learning) با Tensorflow و keras COUPON-5B37A اعتبار تا: 22 خرداد م…
کد تخفیف 50 درصدی GNN علاوه بر کدهای قبلی فعال شد: gnn_coupon50 https://class.vision/product/graph-neural-network/
Showing the 12 most recent of 20 posts we hold for @class_vision. 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 — 8,695 of 1,151,006entries 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.
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.
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.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“🚀 کلاسویژن | یادگیری هوش مصنوعی از پایه تا پیشرفته” (@class_vision), 2,996 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/class_vision.
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.