SubscribersHow many subscribers the channel has now. The wave shows subscribers at each point of the period. The change is against the start of the period.40▲ 471.4 %+33 for the period
ViewsHow many views the posts published in the period have now. These are not views per day: MAX does not report how many views there were yesterday. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.131▼ 81.6 %was 772
ReactionsHow many reactions the posts published in the period have. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.5▼ 66.1 %was 16
MentionsHow many times other channels mentioned the channel: links and reposts, excluding advertising posts. The bigger the circle, the more mentions at that point of the period. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.61▼ 18.3 %was 76with a subscription
RepostsHow many times other channels reposted this channel's posts (excluding advertising posts). Reposts are also counted as mentions. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.28▲ 14.1 %was 25after signing in
Average post reachHow many views one post gets on average. Only posts older than two days are counted: views of fresh posts are still growing. Points with fresh posts are dashed with hollow dots: the reach of all posts right now, it will still grow.5 535▲ 2.9 %was 5 381after signing in
ERRWhat share of subscribers sees an average post: average reach ÷ subscribers × 100 %. The line shows ERR at each point of the period, the dashed line — ERR of the previous period of the same length. Points with posts younger than two days are hollow dots on the dashed end of the line.29.0 %▲ 0.1 ppdashed line — was 28.9 %after signing in
Engagement ERHow often readers react to posts: reactions ÷ views × 100 %. The tick on the bar is the previous period.2.80 %▼ 0.2 pp
Posts per dayHow many posts are published per day on average. Each cell is a point of the period: the darker, the more posts per day. The percentage is the change in the daily average: the current period is still running (today is not over yet), so it is compared with the previous one by pace rather than by total. “Was” is the whole previous period of the same length.4.3▼ 7.5 %was 4.7after signing in
Ad shareWhat share of the period's posts looks like advertising: erid labeling, ad links and other signs. The scale shows the ad load by the quality index thresholds: up to 10 % — low, up to 25 % — moderate, up to 50 % — high, above — very high. A growing share is marked red.3.9 %▲ 1.8 pp
TrendTop — subscribers at the end of each point of the period; bottom — growth per point: green means more subscribers, red means fewer. Above the growth chart — the biggest gain and the biggest loss. MAX does not report how many people subscribed and unsubscribed separately.
Audience growth
+33subscribers in the period
+18 biggest gain · 23 Oct 2026
Channel scoreA channel score from 0 to 100 made of five parts: audience, growth integrity, ad load, trust and calculation reliability. Each bar shows how many points the part earned out of its maximum. The index is recalculated every night; channels are compared with similar ones of the same category and size.
ReachHow many views the posts published at each point of the period have now (not views per day). The record is labeled; the point with today is paler — the day is not over yet. Average post reach — posts older than two days.
Views and reach
709 891views in the period▼ 5.4 %
Average post reach — 5 535 views (posts older than two days).
EngagementER — reactions divided by views, in percent — for the posts of each point of the period. The dashed line is ER for the whole period. The change is in percentage points against the previous period of the same length.
CitationsThe citation index (CI) shows how often and by which channels this channel is mentioned over the last 30 days, excluding advertising posts. The level is its place among similar channels. The line shows CI at each point of the period (for a week or month — the average over its days).
The citation index has not been calculated yet: it will appear after the nightly calculation once other channels mention the channel.
RhythmHow many posts are published on average in each hour of each weekday, Moscow time: the darker the cell, the more posts. “Best time” — the hours when posts older than two days have the highest average reach.
When and how much it posts
MonTueWedThuFriSatSun
036912151821
Best time:09:0018:00hours when posts get the highest average reach
FormatsWhat the feed is made of. Each post has one format, by priority: repost, video, photo, link, text. The bar and percentages show the share of posts of each format; on the right — average reach of one post of the format (posts older than two days), the small bar compares it with the most viewed format.
Post formats
100 posts
Reposts99 %6 168
Video2121 %7 513
Photos3838 %5 699
Links1212 %5 239
Text2020 %7 626
On the right — average reach of one post of the format.
PostsEach dot is a post in the period: horizontally — publication date, vertically — views, dot size — reactions, color — format. This shows hits, flops and how reach changes. For large channels, the 100 most viewed posts and an even sample of the rest are shown — no more than 1,500 dots.
Every post is a dot
Higher means more views, bigger means more reactions. Click a dot to open the post.
VideoPhotosOthersize — reactionsZoom with the + and − buttons, a pinch or Ctrl + mouse wheel; drag a zoomed chart to move it
SummaryTotals for the selected period: how many posts were published, how many views and reactions they have now and the average post reach. Views are the current views of posts published on those days, not views per day. The change is against the same span before the period, if statistics cover it.
Period totals
Click a metric to see it across the period below
Viewstoday — the day is not over yetPoints with posts younger than two days are pale and dashed: their views are still growing.
AdsWhat share of the period's posts looks like advertising: erid labeling, ad links and other signs. The detector is cautious, so the real share is usually higher. The scale shows the ad load by the quality index thresholds. Below — the average reach of an ad post and a regular post, and who the channel advertises (sites that ad links lead to).
What worksPosts of the period with the most views. The bar shows views relative to first place. The preview is the post's image; for a post without an image — the channel avatar. Views are the post's current count.
RhythmHow many posts were published each day of the period (pale bars) and the 7-day average (line): you can see whether the channel is speeding up or slowing down. Today is not over yet, so its average is calculated up to yesterday.
Posts by day
Pale bars are days, the line is the 7-day average: you can see whether the channel is speeding up or slowing down
Posts per day7-day average
Data updated at 10:54 Moscow time. Views are the current counts of posts published on those days; average reach counts posts older than two days.
How the quality index is calculated
Django 5 в примерах: Разрабатывайте мощные и надежные веб-приложения на Python с нуля
Автор: Меле А.
Перед вами 5-е издание бестселлера, в котором показана пошаговая разработка полнофункциональных веб-приложений с аутентификацией, системами управления контентом, обработки платежей, RESTful API и прочими функциональными возможностями. Излагаются основные принципы Django, включая модели, объектно-реляционный преобразователь (ORM), представления, шаблоны, URL-адреса, формы, аутентификацию, сигналы и промежуточные программные компоненты.
Работа с Django рассматривается на примере четырех проектов: приложения для ведения блога, социального веб-сайта, приложения для электронной коммерции и платформы для электронного обучения. По мере чтения вы научитесь: использовать различные модули Django для решения конкретных задач; интегрировать сторонние приложения Django в свой проект; разрабатывать сложные веб-приложения с использованием Redis, Postgres, Celery/RabbitMQ и Memcached; настраивать производственную среду с помощью Docker Compose; разрабатывать RESTful API с помощью Django Rest Framework (DRF); реализовывать полнотекстовые поисковые системы, потоки активности пользователей, платежные шлюзы и рекомендательные механизмы; создавать реально-временные асинхронные (ASGI) приложения с помощью Django Channels и WebSockets. Книга предназначена для читателей с базовыми знаниями Python и программистов, переходящих с других веб-фреймворков, планирующих освоить Django.
Предполагается, что читатель обладает некоторыми знаниями в области HTML и jаvascript.
Разработка приложений на базе больших языковых моделей
Автор: Сухас Пай
Книга посвящена практическим аспектам проектирования и разработки приложений на основе больших языковых моделей (LLM). Рассматриваются внутреннее устройство и архитектура трансформеров, методы подготовки данных для обучения и дообучения, а также подходы к адаптации предобученных моделей под конкретные задачи и предметные области.
Подробно разобраны техники тонкой настройки, доменной адаптации и оптимизации вывода, а также современные парадигмы применения LLM — генерация с дополненной выборкой (RAG), интеллектуальные агенты и интеграция моделей с внешними инструментами и данными. Особое внимание уделено типичным проблемам и отказам, возникающим при переходе от прототипов к полноценным продуктам, и практическим рекомендациям по преодолению подобных ситуаций.
Цифровые приключения. Как программируют компьютеры
Автор: Тулка Т.
Благодаря забавным иллюстрациям и увлекательным заданиям эта книга о приключениях маленького робота сделает сложные идеи простыми для понимания. По мере развития сюжета дети овладеют основами программирования и приобретут навыки решения задач с помощью кода.
Увлекательное интерактивное приключение пробудит в них интерес к информатике и языкам программирования и покажет, насколько безграничны возможности современных технологий.
Данная книга представляет собой фундаментальное и исчерпывающее введение в компьютерное зрение и робототехнику. В ней рассмотрен широкий круг тем, включая цветное зрение, передовые методы сегментации, деформацию изображения, стереозрение, оценку местоположения, глубокое обучение, групповую коррекцию и визуальную одометрию. Уникальной особенностью является объединение всех ключевых концепций компьютерного зрения и управления роботами в одном томе.
Материал книги сопровождается примерами на основе портированного на Python популярного пакета Robotics Toolbox for MATLAB®, что позволяет закрепить знания при помощи нескольких строк кода.
Издание будет полезно читателям с разным уровнем подготовки – от студентов и аспирантов, изучающих робототехнику, до опытных инженеров и исследователей, желающих углубить и систематизировать свои знания.
Necessary cookies keep the site working and secure: sign-in, form protection, language, theme and others. Yandex Metrica analytics cookies and Yandex Advertising Network ad cookies are enabled only with your consent. By clicking “Accept all” you give consent to processing of cookie data; see the Personal Data Processing Policy for details.
