Machine Learning with Python
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
Больше📈 Аналитический обзор Telegram-канала Machine Learning with Python
Канал Machine Learning with Python (@codeprogrammer) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 67 902 подписчиков, занимая 2 401 место в категории Образование и 4 810 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 67 902 подписчиков.
Согласно последним данным от 13 июля, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 89, а за последние 24 часа — -8, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.73%. В первые 24 часа после публикации контент обычно набирает 1.57% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 1 175 просмотров. В течение первых суток публикация набирает 1 063 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
- 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 14 июля, 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.
Загрузка данных...
| Дата | Привлечение подписчиков | Упоминания | Каналы | |
| 13 июля | +5 | |||
| 12 июля | +28 | |||
| 11 июля | +12 | |||
| 10 июля | +12 | |||
| 09 июля | +22 | |||
| 08 июля | +22 | |||
| 07 июля | +14 | |||
| 06 июля | +24 | |||
| 05 июля | +19 | |||
| 04 июля | +17 | |||
| 03 июля | +17 | |||
| 02 июля | +20 | |||
| 01 июля | 0 |
| 2 | Diving deep into Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP. 🤖🧠
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| 7 | Reinforcement Learning Methods and Tutorials
In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.
Learning Resources: https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow
Here's a collection of simple materials on methods and practical guides, covering both basic reinforcement learning algorithms and modern, recently developed, and updated advanced algorithms. | 2 545 |
| 8 | 🚀 Looking for a portfolio-ready NLP project?
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It’s a practical project for anyone preparing for an ML/DS role, with no deep learning required. I walk through the entire workflow step by step:
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| 9 | Нет текста... | 2 247 |
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