Первый автограф
👍2
Signed Ruslan Senatorov | Research Computer Vision & Neural Networks

Channel
@SENATOROVAI
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
451subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003534416268 |
|---|---|
| Type | Channel |
| Username | @SENATOROVAI |
| Description | Написать в личные сообщения @SenatorovLive Школа DATA SCIENCE для любого уровня https://senatorovai.com Курсы t.me/RuslanSenatorov/2463 DS проекты @SenatorovFreelance Основной канал @RuslanSenatorov Ютуб youtube.com/SENATOROV |
| Created | Between 1 December 2025 and 31 May 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 28 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/SENATOROVAI |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 05:01 | 451 | no change |
| 7 Aug 2026, 12:17 | 451 | first reading |
11 posts held, back to 20 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 1 pageof 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 4 of 6 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 5 August 2026 |
|---|---|
| Posts held | 11 (20 July 2026 – 5 August 2026) |
| Views total | 1,418 |
| Reactions total | 6 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 05:01 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.
Lifetime counters from Telegram’s own channel header, read 8 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.
Measured directly from 2 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.
18 reactions across 7 posts, in 5 distinct kinds. The most used accounts for 22.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 4 | 22.2% | |
| 👍 | 4 | 22.2% | |
| 💊 | 4 | 22.2% | |
| 🔥 | 4 | 22.2% | |
| 🎉 | 2 | 11.1% |
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 8 of the 11 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 18reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 20 July 2026 to 5 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.
Первый автограф
👍2
Signed Ruslan Senatorov | Research Computer Vision & Neural Networks
Посчастливилось встретить нашего Учителя и получить автограф сертификата с Udemy по Open Source
🔥3
Signed Anton Surikov
Вот такие крутые у меня студенты
Signed Ruslan Senatorov | Research Computer Vision & Neural Networks
Я в Москве.
🔥1
Signed Ruslan Senatorov | Research Computer Vision & Neural Networks
Optimization of Parameters and Comparison of Models in Regression Analysis Regression Analysis: Regression analysis in modern science and business has long ceased to be merely a tool for describing data. Today, it is a complex engineering challenge where success depends not only on the choice of algorithm but also on the fine-tuning of its "internal gears"—hyperparameters. However, the pursuit of accuracy on the trai…
Signed Виктор Виноградов
Hi everyone. My name is Mikhail, and I’m from Russia. I’m an intern on the course. I previously studied Python and SQL on my own. I found out about this course through a Telegram channel. My background is in accounting and economics, and my English level is B1. My goal is to learn Data Science — specifically the analytical approach to machine learning, so I can work in this field. I really enjoy walking and visiting …
Signed Михаил Каневский
Всем привет! Недавно прошёл соревнование на Kaggle по предсказанию цен на дома и хочу поделиться впечатлениями. В рамках задачи нужно было с нуля выполнить EDA-анализ, обработать пропуски, закодировать категориальные признаки, стандартизировать числовые переменные, прологарифмировать целевую переменную (цену дома), а также обучить несколько моделей и выбрать среди них лучшую. Мой лучший скор составил 0.1258 — это зн…
❤2👍2💊1
Signed Виктор Виноградов
Posted without readable text
Компания SenatorovAI выполняет проекты по 45 направлениям в сфере информационных технологий — от решения отдельных технических задач до разработки и сопровождения полноценных IT-продуктов. Основные направления работы: — веб-, мобильная и десктопная разработка; — разработка SaaS-приложений и MVP; — искусственный интеллект и Data Science; — машинное обучение, NLP и Computer Vision; — чат-боты и AI-ассистенты; — авто…
❤1
Signed Ruslan Senatorov | Research | Computer Vision | Neural Networks
Hello everyone! My name is Kirill Levin. I am from Belarus. I am an intern at the school. My English level is A2. I found the school from a YouTube video. Before this, I studied Machine Learning and Python by myself at a basic level. My goal is to grow professionally and start earning money with my skills. I am a third-year university student, and my major is Applied Mathematics. In my free time, I love playing volle…
🎉2💊2❤1
Signed Kirill
ИЩЕМ ФРИЛАНСЕРОВ. Компания @SenatorovAI быстро расширяется, проектов на всех не хватает, а зарабатывать все хотят, поэтому мы приглашаем к долгосрочному сотрудничеству опытных фрилансеров с развитыми профилями и высоким рейтингом, чтобы через ваш аккаунт брать проекты, ВАША КОМИССИЯ С КАЖДОГО ПРОЕКТА 30% Формат сотрудничества: вы откликаетесь через свой аккаунт на бирже фриланса, а наша команда отвечает за их профе…
💊1
Signed Ruslan Senatorov | Research | Computer Vision | Neural Networks
Showing the 11 most recent of 11 posts we hold for @SENATOROVAI. 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 — 184,338 of 1,625,404entries 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.
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.
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 8 August 2026 — this entry's latest reading, not the date you are reading this.
“SenatorovAI | IT-разработка и консалтинг | Школа Data Science Руслана Сенаторова” (@SENATOROVAI), 451 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/SENATOROVAI.
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.