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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 67 826 подписчиков, занимая 2 419 место в категории Образование и 4 901 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 67 826 подписчиков.

Согласно последним данным от 23 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 107, а за последние 24 часа — 23, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 4.73%. В первые 24 часа после публикации контент обычно набирает 1.30% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 3 210 просмотров. В течение первых суток публикация набирает 884 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 4.
  • 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 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 Образование.

67 826
Подписчики
+2324 часа
-367 дней
+10730 день
Архив постов
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Thanks 🙏

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Curated list of distributed systems papers and books 📚📖 https://github.com/theanalyst/awesome-distributed-systems ✨ Join Be
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My favorite way to work with multiple filters in pandas.Series — not a chain of .loc, but a single mask. 🐼 The chain looks neat, but breaks on real data and easily gives unexpected results:
s = pd.Series([10, 15, 20, 25, 30])
s.loc[s > 20].loc[s % 2 == 1]
The problem is that the second .loc again looks at the original s, not the already filtered result. The logic gets messy. 🤯 It's more reliable to gather everything into one expression:
s = pd.Series([10, 15, 20, 25, 30])

mask = (s > 20) & (s % 2 == 1)
result = s.loc[mask]
One mask, one point of truth. ✅ It's easier to debug. Fewer surprises when the code grows. 🚀 #Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

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