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Channel

Tensorflow(@CVision)

@cvision

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry

15,061subscribers

+53 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001072608535
TypeChannel
Username@cvision
Created4 November 2016 — measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live11 November 2026
Measurements held58
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/cvision

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 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.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

No sample pairs were kept for this entry. The counts below were measured, but without the pairs there is nothing here for you to open and check, so treat the relationship as recorded rather than demonstrated.

Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@llm_huggingface7 (7/7 hand-verifiable sample passed)1.00under a minutethis entry (4–3)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 1 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.

“Published first” means first in this corpus. We hold 34 comparable posts for this entry, running 16 July 2026 to 10 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 2 channels, the one whose matching posts we hold earliest is @llm_huggingface. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_mutual, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Channels linked by matching posts

This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

15,00715,13215,069.56 August 2026 — 15,008 subscribers6 August 2026 — 15,012 subscribers7 August 2026 — 15,007 subscribers8 August 2026 — 15,016 subscribers9 August 2026 — 15,034 subscribers10 August 2026 — 15,042 subscribers11 August 2026 — 15,053 subscribers12 August 2026 — 15,067 subscribers13 August 2026 — 15,075 subscribers15 August 2026 — 15,082 subscribers16 August 2026 — 15,093 subscribers19 August 2026 — 15,096 subscribers20 August 2026 — 15,099 subscribers21 August 2026 — 15,105 subscribers22 August 2026 — 15,113 subscribers24 August 2026 — 15,118 subscribers25 August 2026 — 15,114 subscribers26 August 2026 — 15,113 subscribers27 August 2026 — 15,112 subscribers28 August 2026 — 15,109 subscribers29 August 2026 — 15,100 subscribers30 August 2026 — 15,103 subscribers31 August 2026 — 15,104 subscribers4 September 2026 — 15,111 subscribers6 September 2026 — 15,107 subscribers9 September 2026 — 15,119 subscribers11 September 2026 — 15,115 subscribers13 September 2026 — 15,128 subscribers15 September 2026 — 15,126 subscribers17 September 2026 — 15,121 subscribers26 September 2026 — 15,132 subscribers4 October 2026 — 15,118 subscribers9 October 2026 — 15,106 subscribers13 October 2026 — 15,099 subscribers14 October 2026 — 15,095 subscribers15 October 2026 — 15,094 subscribers16 October 2026 — 15,096 subscribers17 October 2026 — 15,090 subscribers18 October 2026 — 15,093 subscribers19 October 2026 — 15,092 subscribers20 October 2026 — 15,093 subscribers22 October 2026 — 15,089 subscribers23 October 2026 — 15,084 subscribers24 October 2026 — 15,083 subscribers25 October 2026 — 15,084 subscribers26 October 2026 — 15,076 subscribers27 October 2026 — 15,078 subscribers29 October 2026 — 15,079 subscribers30 October 2026 — 15,075 subscribers31 October 2026 — 15,077 subscribers1 November 2026 — 15,076 subscribers2 November 2026 — 15,078 subscribers4 November 2026 — 15,076 subscribers5 November 2026 — 15,072 subscribers6 November 2026 — 15,074 subscribers8 November 2026 — 15,068 subscribers9 November 2026 — 15,063 subscribers11 November 2026 — 15,061 subscribers15,0616 August 202611 November 2026
58 measurements spanning 97 days, net +53. 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 14,988–15,151 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 58
Measured (UTC)SubscribersChange
11 Nov 2026, 07:0615,061-2
9 Nov 2026, 10:5015,063-5
8 Nov 2026, 00:1915,068-6
6 Nov 2026, 00:1015,074+2
5 Nov 2026, 00:5715,072-4
4 Nov 2026, 03:5715,076-2
2 Nov 2026, 07:0915,078+2
1 Nov 2026, 08:5515,076-1
31 Oct 2026, 08:4015,077+2
30 Oct 2026, 09:4515,075-4
29 Oct 2026, 06:2815,079+1
27 Oct 2026, 08:2615,078+2
26 Oct 2026, 06:1915,076-8
25 Oct 2026, 05:3715,084+1
24 Oct 2026, 07:5415,083-1
23 Oct 2026, 04:5015,084-5
22 Oct 2026, 05:2015,089-4
20 Oct 2026, 21:3915,093+1
19 Oct 2026, 20:3915,092-1
18 Oct 2026, 20:5615,093first reading

Engagement

42 posts held, back to 16 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 71 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
17.3%
avg views ÷ 15,061 subscribers
Avg views / post
2,600
10 posts measured
Reaction rate
0.434%
reactions ÷ views · ER floor
Posts in window
10
of 42 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 November 2026
Posts held42 (16 July 2026 – 11 November 2026)
Views total26,025
Reactions total113
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 07:01 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
9m 36s
Average length
1m 55s

Measured directly from 5 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

603 reactions across 40 posts, in 12 distinct kinds. The most used accounts for 55.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤33755.9%
🔥8313.8%
👍6811.3%
👏325.31%
❤‍🔥152.49%
👌142.32%
🙏142.32%
🤯132.16%
👀101.66%
😱81.33%
🤔50.829%
⚡40.663%

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 42 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 627 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 42 most recent posts we hold, published 16 July 2026 to 11 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: 5 of 10 posts held from the last 30 days (50.0%) 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).

11 Nov 2026, 06:40 UTC255 views3 reactionsread 11 November 2026

این کارگاه از آپارات نیز لایو منتشر خواهد شد

🙏3

10 Nov 2026, 07:39 UTC≈1,190 views15 reactionsread 11 November 2026
Video

🤯 وقتی هوش مصنوعی از صفر یک سیستم‌عامل می‌سازه! یکی از شگفت‌انگیزترین آزمایش‌های آنتروپیک با مدل Claude Fable 5.2، ساخت یک سیستم‌عامل کامل از یک پوشه خالی بوده! 💻 در این آزمایش، مدل با هماهنگ‌کردن بیش از ۱۰۰۰ ایجنت هوش مصنوعی، طی ۸ روز به‌صورت شبانه‌روزی کدنویسی، تست و بازبینی انجام داده. 🔥 نتیجه، یک سیستم‌عامل آزمایشی قابل اجرا روی لپ‌تاپ بوده که امکانات زیر رو داره: 🔹 هسته اختصاصی سیستم‌عامل 🔹 درایورهای دیسک، کیب…

🤯11❤4

Signed 𝘴𝘪𝘯𝘢

10 Nov 2026, 07:37 UTC≈1,150 views6 reactionsread 11 November 2026
Photo

🚀 آنتروپیک با معرفی دو مدل جدید، قدرت هوش مصنوعی رو به سطح تازه‌ای رسوند! شرکت آنتروپیک از دو مدل قدرتمند Claude Fable 5.2 و Claude Mythos 5.2 رونمایی کرده که برای حل مسائل پیچیده برنامه‌نویسی، مهندسی و تحقیقات علمی طراحی شدن. 🔥 چند مورد از قابلیت‌های چشمگیر این مدل‌ها: 🔹 افزایش سرعت تولید پاسخ تا ۳۰ درصد نسبت به نسل قبل 🔹 عملکرد بهتر در کدنویسی، استدلال و تحلیل تصاویر 🔹 پیشرفت قابل‌توجه در امنیت سایبری و شناسایی آ…

🔥6

Signed 𝘴𝘪𝘯𝘢

9 Nov 2026, 17:59 UTC≈1,370 views6 reactionsread 11 November 2026
Forwarded from @mvip2026Video

🧠 کارگاه آموزشی W2 | مدل‌های بینایی-زبانی (VLM) 🌐 برای ثبت نام در کنفرانس کلیک کنید. @mvip2026 @kashan_ict

🔥6

8 Nov 2026, 12:32 UTC≈1,810 views5 reactionsread 11 November 2026
Photo

💎 با مکتب‌خونه، بورسیه دانشگاه هاروارد شو! 🎉 مکتب‌خونه به مناسبت تولد ۱۵ سالگیش یک قرعه‌کشی ویژه برگزار کرده؛ از بورسیه آموزشی دانشگاه هاروارد به ارزش ۲۰۰۰ دلار گرفته تا اشتراک ChatGPT Plus و اشتراک مکتب‌خونه. 🔥 علاوه بر جوایز قرعه‌کشی، تخفیف‌های ویژه تولد مکتب‌خونه هم فعال شده: ▪️ ۸۰٪ تخفیف اشتراک یک‌ساله ▪️ تا ۷۰٪ تخفیف دوره‌های آموزشی 🧠 اگه به یادگیری ماشین و یادگیری عمیق علاقه داری یا با ابزارهایی مثل TensorF…

❤2👍1👏1🤯1

5 Nov 2026, 07:43 UTC≈2,810 views12 reactionsread 11 November 2026
Photo

🚀 اوپن‌ای‌آی از مدل جدید تولید تصویر خودش رونمایی کرد! مدل GPT-Image 2.6 با سرعت بیشتر، ویرایش دقیق‌تر و قابلیت جذاب ساخت تصاویر متحرک GIF معرفی شد. 🔥 مهم‌ترین قابلیت‌های این نسخه: 🔹 سرعت بالاتر: تولید تصاویر تا ۵۰٪ سریع‌تر از نسخه قبلی انجام می‌شه. 🔹 ساخت تصاویر متحرک: حالا می‌تونید فقط با یک پرامپت، تصاویر متحرک با فرمت GIF بسازید. 🔹 ویرایش هوشمندتر: امکان تغییر بخش‌های مشخص تصویر با حفظ جزئیات، ظاهر کاراکترها و …

👍6❤4🔥2

Signed 𝘴𝘪𝘯𝘢

4 Nov 2026, 16:21 UTC≈2,730 views12 reactionsread 11 November 2026

مستندات فارسی شده opencv : https://learnopencv.ir/docs/ همچنین لینک به این مستندات در نوت بوک های کورس مکتب خونه اضافه شد

❤10❤‍🔥1🤔1

1 Nov 2026, 06:10 UTC≈5,640 views38 reactionsread 11 November 2026
Photo

نسخه فارسی و تحت وب Deep Learning with Python ویرایش 3 https://introtodeeplearning.ir/books/dlwp/

❤32🙏5❤‍🔥1

22 Oct 2026, 11:01 UTC≈4,700 views6 reactionsread 11 November 2026

کسانی که تازه شروع کردند، میدونند که پیش نیاز اکثر فریم ورکهای مرتبط با هوش مصنوعی پایتونه، دوست داشتید در کانال بالا عضو شده و از سایتش مطالب را مرور کنید @PyLab

❤6

22 Oct 2026, 10:59 UTC≈4,370 views10 reactionsread 11 November 2026
Forwarded from @PyLabPhoto

🐍 چالش پایتون ۱ | += روی لیست؛ تغییر یا ساختن؟ خروجی این کد چیست؟ قبل از اجرا، خط به خط فکر کن؛ حدس نزن! 🤔 a = [1, 2, 3] b = a b += [4] b = b + [5] print(a, b) 👇 جوابت را در کوییز زیر بزن، بعد توضیح کامل را در سایت بخوان. #چالش_پایتون #پایتون #Python 📢 @PyLab

👍8❤2

20 Sept 2026, 05:19 UTC≈6,870 views23 reactionsread 11 November 2026

‏🎯 Jev‏ کجا به درد می‌خورد و کجا نه؟ ‏Jev‏ بیشتر از اینکه جای GPT‏ یا Claude‏ را بگیرد، می‌تواند یک «لایه‌ی تصمیم‌گیری» سریع و ارزان باشد. یعنی برای کارهای کوچک و پرتعداد که الان بی‌خودی برای هرکدام یک مدل بزرگ صدا می‌زنیم. ‏تقسیم کار پیشنهادی (Separation of Concerns‏): ‏• تصمیم‌های کوچک و پرتعداد ← Jev ‏• تحلیل، reasoning‏ و تولید محتوا ← GPT / Claude / Gemini‏ ‏• قوانین قطعی، محاسبات و محدودیت‌های حساس ← Code‏ ‏•…

❤17👏6

20 Sept 2026, 05:11 UTC≈4,480 views8 reactionsread 11 November 2026

‏🧠 Jev از TypeSafe AI‏؛ مدلی که متن نمی‌نویسد، تصمیم می‌گیرد ‏TypeSafe AI روز ۱۵ سپتامبر ۲۰۲۶ با ۴۰ میلیون دلار سرمایه معرفی شد و اولین مدلش، Jev‏، را در حالت early access‏ (با waitlist‏) عرضه کرد. بنیان‌گذار و CEO آن، Diogo Almeida‏، سابقه‌ی کار در OpenAI‏ دارد و از نویسندگان مقاله‌ی InstructGPT‏ است. ‏ایده جالب است: به‌جای ساختن یک LLM‏ بهتر برای تولید متن، مدلی بسازیم که مستقیم برای تصمیم‌گیری داخل نرم‌افزار طرا…

❤5👏3

Showing the 12 most recent of 42 posts we hold for @cvision. 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 recorded as deleted after publishing

We recorded 1 post on @cvision as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.

A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.

First seen missing
27 August 2026
Most recent seen missing
27 August 2026
Median time before seen missing
45 hours
Seen missing in the last 30 days
0

Forward network

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.

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.

آقای هوش مصنوعی
@MrArtificialintelligence · 20,689
Telegram ranks this channel #5 of 94 here — alongside 93 others — read 26 September 2026
DLeX: AI Python
@ai_python · 21,298
Telegram ranks this channel #5 of 94 here — alongside 93 others — read 23 September 2026
مجله هوش مصنوعی
@HomeAI · 32,870
Telegram ranks this channel #6 of 91 here — alongside 90 others — read 5 September 2026
هوش مصنوعی |یادگیری ماشین| علم داده
@Ai_Tv · 26,535
Telegram ranks this channel #12 of 94 here — alongside 93 others — read 12 September 2026
Machine Learning | یادگیری ماشین
@MachineLearning_ir · 34,710
Telegram ranks this channel #12 of 90 here — alongside 89 others — read 3 September 2026
Geek Alerts
@geekalerts · 18,647
Telegram ranks this channel #13 of 89 here — alongside 88 others — read 4 October 2026
اخبار هوش مصنوعی
@Ai_NewsTv · 27,210
Telegram ranks this channel #17 of 88 here — alongside 87 others — read 10 September 2026
دانش، آگاهی
@daneshagahi · 28,685
Telegram ranks this channel #21 of 95 here — alongside 94 others — read 10 September 2026
Programming Resources
@pythony · 19,710
Telegram ranks this channel #23 of 95 here — alongside 94 others — read 30 September 2026
هوش مصنوعی در پژوهش
@AI_in_Research · 305,648
Telegram ranks this channel #24 of 92 here — alongside 91 others — read 19 August 2026
AvalAI | هوش مصنوعی
@aval_ai · 24,607
Telegram ranks this channel #34 of 92 here — alongside 91 others — read 13 September 2026
عصر گویش | هوش مصنوعی
@asrgooyeshpardaz · 99,519
Telegram ranks this channel #36 of 89 here — alongside 88 others — read 24 August 2026
آموزش مکالمه زبان انگلیسی
@eng_asan · 18,697
Telegram ranks this channel #37 of 49 here — alongside 48 others — read 4 October 2026
IELTSFamily | بيان برتر
@ieltsfamily · 21,312
Telegram ranks this channel #48 of 87 here — alongside 86 others — read 23 September 2026
نخبگان ایران
@bmniran · 22,153
Telegram ranks this channel #52 of 94 here — alongside 93 others — read 23 September 2026
Kooshiar
@kooshiar3 · 25,589
Telegram ranks this channel #55 of 93 here — alongside 92 others — read 14 September 2026
IELTS Channel
@PARGARIELTS · 25,790
Telegram ranks this channel #55 of 87 here — alongside 86 others — read 14 September 2026
ApplyKite
@ApplyIR2UK · 38,939
Telegram ranks this channel #55 of 88 here — alongside 87 others — read 31 August 2026
Dr Ahmadian
@drmjahmadian · 90,427
Telegram ranks this channel #56 of 93 here — alongside 92 others — read 17 August 2026
مغز آینده |NextBrain
@NextBrain_ir · 19,754
Telegram ranks this channel #60 of 90 here — alongside 89 others — read 29 September 2026
پیشنهادهایی برای #اپلای #applyabroad
@safarnamee7 · 33,116
Telegram ranks this channel #60 of 88 here — alongside 87 others — read 4 September 2026
پایتون | Data Science | Machine Learning
@Python4all_pro · 24,131
Telegram ranks this channel #64 of 91 here — alongside 90 others — read 16 September 2026
ژورنال آکادمیک
@journalacademic · 26,504
Telegram ranks this channel #64 of 78 here — alongside 77 others — read 12 September 2026
Anki Decks
@AlienAnkiDecks · 19,699
Telegram ranks this channel #69 of 87 here — alongside 86 others — read 3 October 2026

This channel appears in 40 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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.

“Tensorflow(@CVision)” (@cvision), 15,061 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/cvision.

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.