Machine Learning

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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

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Сеть:Machine Learning with Python Сирия232 Технологии и приложения3 398...

📈 Аналитический обзор Telegram-канала Machine Learning

Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 100 подписчиков, занимая 3 398 место в категории Технологии и приложения и 232 место в регионе Сирия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 100 подписчиков.

Согласно последним данным от 23 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 379, а за последние 24 часа — 30, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.92%. В первые 24 часа после публикации контент обычно набирает 1.16% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 770 просмотров. В течение первых суток публикация набирает 466 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
Тематические интересы: Контент сосредоточен на ключевых темах, таких как distance, insidead, gpu, learning, degree.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Благодаря высокой частоте обновлений (последние данные получены 24 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.

40 100

Подписчики

+3024 часа

+337 дней

+37930 день

770

Просмотры поста

~ 46624 часа

~ 62048 часов

1.92%

Коэффициент вовлеченности

~ 3

Постов в день

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Архив постов

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Transformers in Action 2026

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📌 AI in Multiple GPUs: Point-to-Point and Collective Operations 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-13 | ⏱️ Read time: 10 min read Learn PyTorch distributed operations for multi GPU AI workloads #DataScience #AI #Python

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📌 The Evolving Role of the ML Engineer 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2026-02-13 | ⏱️ Read time: 5 min read Stephanie Kirmer on the $200 billion investment bubble, how AI companies can rebuild trust, and… #DataScience #AI #Python

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📌 How to Leverage Explainable AI for Better Business Decisions 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-12 | ⏱️ Read time: 10 min read Moving beyond the black box to turn complex model outputs into actionable organizational strategies. #DataScience #AI #Python

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📌 AI in Multiple GPUs: Understanding the Host and Device Paradigm 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-12 | ⏱️ Read time: 7 min read Learn how CPU and GPUs interact in the host-device paradigm #DataScience #AI #Python

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📌 Building an AI Agent to Detect and Handle Anomalies in Time-Series Data 🗂 Category: AGENTIC AI 🕒 Date: 2026-02-11 | ⏱️ Read time: 13 min read Combining statistical detection with agentic decision-making #DataScience #AI #Python

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📌 Not All RecSys Problems Are Created Equal 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-02-11 | ⏱️ Read time: 9 min read How baseline strength, churn, and subjectivity determine complexity #DataScience #AI #Python

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Repost from Machine Learning with Python

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