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

Сітка:Machine Learning with Python Індія5 078 Освіта2 407...

📈 Аналітичний огляд Telegram-каналу Machine Learning with Python

Канал Machine Learning with Python (@codeprogrammer) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 67 827 підписників, посідаючи 2 407 місце в категорії Освіта та 5 078 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 67 827 підписників.

За останніми даними від 04 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 75, а за останні 24 години на 11, загальне охоплення залишається високим.

Статус верифікації: Не верифікований
Рівень залученості (ER): Середній показник залученості аудиторії становить 2.53%. Протягом перших 24 годин після публікації контент зазвичай збирає 1.84% реакцій від загальної кількості підписників.
Охоплення публікацій: В середньому кожен допис отримує 1 717 переглядів. Протягом першої доби публікація в середньому набирає 1 249 переглядів.
Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 6.
Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як insidead, learning, degree, evaluation, algorithm.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Завдяки високій частоті оновлень (останні дані отримано 05 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

67 827

Підписники

+1124 години

+587 днів

+7530 день

1 717

Перегляди допису

~ 1 24924 години

~ 1 70648 годин

2.53%

Коефіцієнт залучення

~ 3

Дописів на день

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Repost from Machine Learning

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Do you know that Python can shift sequences without slicing and creating new lists? 🤔 When you need to cyclically shift data, many use slicing:

data = data[-1:] + data[:-1]

But deque.rotate() does this at the level of the data structure and usually works more efficiently for cyclical operations. 🚀

q.rotate(1)

A negative value rotates the queue in the other direction. ⬅️

q.rotate(-2)

This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms. 🔄

workers.rotate(-1)

🔥 deque.rotate() allows you to implement cyclical data structures without manual index logic and without creating new lists. 💡 👉 Python Ready | #tip #Python #Programming #Deque #CodingTips #Tech #DevCommunity

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Do you know that Python can shift sequences without slicing and creating new lists? When you need to cyclically shift data, many use slicing:

data = data[-1:] + data[:-1]

But `deque.rotate()

 does this at the level of the data structure and usually works more efficiently for cyclical operations.

``

python q.rotate(1)

A negative value rotates the queue in the other direction.

python q.rotate(-2)

This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms.

python workers.rotate(-1) ` 🔥 `deque.rotate()` allows you to implement cyclical data structures without manual index logic and without creating new lists. #Python #deque #rotate #Programming #Coding #DevTips

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Repost from Machine Learning

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Repost from Machine Learning with Python

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