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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Аналитический обзор Telegram-канала Machine Learning with Python

Канал Machine Learning with Python (@codeprogrammer) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 68 536 подписчиков, занимая 2 402 место в категории Образование и 4 600 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 68 536 подписчиков.

Согласно последним данным от 29 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 74, а за последние 24 часа — -5, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 3.84%. В первые 24 часа после публикации контент обычно набирает 1.47% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 2 629 просмотров. В течение первых суток публикация набирает 1 007 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 9.
  • Тематические интересы: Контент сосредоточен на ключевых темах, таких как insidead, learning, degree, evaluation, algorithm.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Благодаря высокой частоте обновлений (последние данные получены 30 октября, 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 Образование.

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68 536
Подписчики
-524 часа
-847 дней
+7430 дней
Архив постов
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Repost from Machine Learning
🔖 40 NumPy methods that cover 95% of tasks A convenient cheat sheet for those who work with data analysis and ML. Here are c
🔖 40 NumPy methods that cover 95% of tasks A convenient cheat sheet for those who work with data analysis and ML. Here are collected the main functions for:
▶️ Creating and modifying arrays; ▶️ Mathematical operations; ▶️ Working with matrices and vectors; ▶️ Sorting and searching for values.
Save it for yourself — it will come in handy when working with NumPy. tags: #NumPy #Python ➡ @DataScienceM

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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Awesome open-source project to learn more about Generative Adversarial Networks. We found this interactive website that shows
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