27 Jul 2026, 10:50 UTC347 viewsread 8 August 2026
File
اسلایدهای دوره Agentic
Signed Alireza Akhavan
Channel
Deep learning channel
@irandeeplearning
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
4,401subscribers
+2 since we began measuring on 5 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1001053660476 |
|---|---|
| Type | Channel |
| Username | @irandeeplearning |
| Created | Between 1 May 2016 and 31 January 2017— 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 | 3 |
| Confirmed unchanged | 2 times, most recently 12 August 2026 |
| On Telegram | t.me/irandeeplearning |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 9 Aug 2026, 15:14 | 4,401 | +2 |
| 6 Aug 2026, 04:04 | 4,399 | no change |
| 5 Aug 2026, 23:43 | 4,399 | first reading |
Engagement
13 posts held, back to 21 November 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 6 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 7.82%
- avg views ÷ 4,401 subscribers
- Avg views / post
- 344
- 3 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 3
- of 13 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.
| Window | Rolling 30 days · latest post in window 27 July 2026 |
|---|---|
| Posts held | 13 (21 November 2024 – 27 July 2026) |
| Views total | 1,033 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 18:16 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
- 6m 47s
- Average length
- 2m 16s
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.
Recent posts
27 Jul 2026, 10:50 UTC370 viewsread 8 August 2026
Photo
در صورتی که به مدرک مکتبخونه نیاز ندارید، میتوانید کوییزها، و تمرینها و پروژهها را از طریق کانال دانلود کنید: لینک کانال: https://t.me/agentic_llm لینک دوره: https://mktb.me/m6tt/ هنگام خرید، کافیست گزینهی «دسترسی پایه» را تیک بزنید تا فقط به ویدیوها دسترسی داشته باشید و بتوانید با هزینهی کمتری ثبتنام کنید. @agentic_llm
Signed Alireza Akhavan
27 Jul 2026, 10:49 UTC316 viewsread 8 August 2026
Video
🤖 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…
Signed Alireza Akhavan
1 Oct 2025, 14:53 UTC≈1,860 viewsread 8 August 2026
Forwarded from @llm_huggingfaceVideo
🌟 آموزش مدلهای زبانی-تصویری (VLM) با تدریس علیرضا اخوانپور منتشر شد🎉 مردادماه دورهی مدلهای زبانی بزرگ (LLM) در مکتبخونه منتشر شد؛ دورهای که توش یاد میگرفتید مدلهایی مثل ChatGPT یا Gemini چطور آموزش میبینن، چطور کار میکنن و چطور میتونن به زبانهای مختلف – حتی فارسی – پاسخ بدن و ... ♨️حالا نوبت یکی از داغترین موضوعات دنیای AI رسیده: 🔹 مدلهای زبانی-تصویری (VLM) مدلهای زبانی-تصویری (VLM) نسل جدیدی از مدل…
Signed Alireza Akhavan
19 Sept 2025, 06:40 UTC≈1,700 viewsread 8 August 2026
Forwarded from @cvisionPhoto
🚀 نسخه جدید Deep Learning with Python: رایگان + محتوای LLM و GenAI توئیت 16 ساعت پیش François Chollet ویرایش سوم کتاب من با عنوان Deep Learning with Python هماکنون در حال چاپ است و ظرف دو هفته آینده در کتابفروشیها خواهد بود. شما میتوانید آن را همین حالا از آمازون یا انتشارات Manning سفارش دهید. این بار، ما کل کتاب را بهصورت یک وبسایت کاملاً رایگان منتشر میکنیم. برایم مهم نیست اگر این کار باعث کاهش فروش کتا…
Signed Alireza Akhavan
7 Aug 2025, 14:47 UTC≈1,930 viewsread 8 August 2026
Forwarded from @class_vision
🎉 کمپین همدلی در مسیر یادگیری | با مکتبخونه مکتبخونه بیش از ۱۰۰ دوره پرفروش و کاربردی رو در حوزههای مختلف مثل: 💻 برنامهنویسی 🌐 شبکه 🧠 هوش مصنوعی 🗣 زبانهای خارجی 🤝 مهارتهای نرم و کلی حوزه دیگه رو برای مدت محدود کاملاً رایگان کرده! چرا؟ چون یادگیری، امید میده، حال خوب میده، حس پیشرفت میده... 🌱 📚 همه دورههای رایگان اینجان: 🔗 https://mktb.me/txvk/ 💥 خبر خوب دیگه: دورهی محبوب و کاربردی "آموزش پردازش تصویر و…
Signed Alireza Akhavan
25 Jul 2025, 16:46 UTC≈1,960 viewsread 8 August 2026
Forwarded from @llm_huggingfaceVideo
📢دورهی "آموزش هوش مصنوعی مولد با مدلهای زبانی بزرگ (LLM)" منتشر شد🎉🎊 کد تخفیف 50 درصدی ویژه 100 نفر: COUPON-091dc آدرس دوره https://mktb.me/04dr/ 📄سرفصلها: https://t.me/llm_huggingface/18 🔥 برای اطلاع از کدهای تخفیف، همین حالا عضو کانال تلگرام ما بشید: 👇👇👇 @llm_huggingface 👆👆👆 #llm #course #دوره #مدل_زبانی_بزرگ #هوش_مصنوعی #مکتبخونه
Signed Alireza Akhavan
28 May 2025, 19:10 UTC≈4,780 viewsread 8 August 2026
Photo
📊 میزان (MIZAN): جامعترین لیدربورد ارزیابی مدلهای زبانی بزرگ (LLM) در زبان فارسی پس از عرضه بنچمارک FaMTEB برای ارزیابی مدلهای Text Embedding، اینبار دستاوردی تازه در پردازش زبان طبیعی فارسی ✅ برخی ویژگی های میزان: - مقایسه جامع مدلهای روز: ارزیابی دقیق مدلهای متنباز و بسته با هدف ایجاد یک مرجع معتبر برای فارسیزبانان - پوشش ۶ بنچمارک تخصصی: سنجش عملکرد مدلها در چت، پیروی از دستورالعمل، NLU، NLG، استدلال م…
21 May 2025, 17:54 UTC≈1,960 viewsread 8 August 2026
Forwarded from @cvisionPhoto
دیتاست کارت ملی ایرانی https://class.vision/blog/iranian-national-id-card-dataset/ دیتاست شامل ۲٬۰۰۰ تصویر از کارتهای ملی ایرانی است که با اطلاعات هویتی ساختگی ایجاد شدهاند. کارتها با کیفیت چاپ کارتهای واقعی تولید و در شرایط چالشبرانگیز و غیرکنترلشده با دوربینهای موبایل عکسبرداری شدهاند. #دیتاست
Signed Alireza Akhavan
15 May 2025, 08:13 UTC≈2,210 viewsread 8 August 2026
Forwarded from @cvision
آموزش معماری DeepSeek از صفر تا صد، مجموعهای شامل ۲۰ ویدئوی آموزشی این مجموعه شامل ۲۰ جلسه آموزشی هست که مفاهیمی مثل Multi-Head Latent Attention و Mixture of Experts رو با جزئیات کامل بررسی میکنه. 1️⃣ DeepSeek Series Introduction https://youtu.be/QWNxQIq0hMo 2️⃣ DeepSeek Basics https://youtu.be/WjhDDeZ7DvM 3️⃣ Journey of a Token into the LLM Architecture https://youtu.be/rkEYwH4UGa4 4️⃣ Attention Mechanism Exp…
Signed Alireza Akhavan
5 Jan 2025, 05:40 UTC≈2,930 viewsread 8 August 2026
Forwarded from @class_vision
وبینار رایگان: تفسیرپذیری شبکههای عصبی گرافی ویدویها _کدها + اسلاید این وبینار روی سایت قرار گرفت https://class.vision/product/explainable-ai-graph-neural-networks/ @class_vision @cvision
Signed Alireza Akhavan
19 Dec 2024, 08:27 UTC≈2,740 viewsread 8 August 2026
Forwarded from @class_visionPhoto
وبینار رایگان: تفسیرپذیری شبکههای عصبی گرافی این وبینار بهصورت آنلاین برگزار میشود. 🗓 زمان: پنج شنبه، ۱۳ دی ۱۴۰۳ ⏰ ساعت: 10 الی 12 صبح https://class.vision/product/explainable-ai-graph-neural-networks/
Signed Alireza Akhavan
Showing the 12 most recent of 13 posts we hold for @irandeeplearning. 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
Citation-graph rank — 253,855 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.
Forward network
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.
Mentions
Named by 3 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 9 August 2026 — this entry's latest reading, not the date you are reading this.
“Deep learning channel” (@irandeeplearning), 4,401 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/irandeeplearning.
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.