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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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📈 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 68 566 підписників, посідаючи 2 405 місце в категорії Освіта та 4 691 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 68 566 підписників.

За останніми даними від 26 жовтня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 211, а за останні 24 години на -16, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 3.52%. Протягом перших 24 годин після публікації контент зазвичай збирає 1.51% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 2 414 переглядів. Протягом першої доби публікація в середньому набирає 1 035 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 27 жовтня, 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.

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68 566
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-1624 години
-507 днів
+21130 днів
Архів дописів
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Repost from Machine Learning
I found a great resource for interactive learning about machine learning and AI – VizLearn. You can experiment with gradient descent, SVM, PCA, the Bayesian method, BPE tokenization, Q/K/V, KV-cache, quantization, and much more. You can change the input data and see how the calculations themselves change. It's free and doesn't require registration. https://vizlearn.in https://t.me/MachineLearning9

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A collection of explanations for key concepts and scientific papers in machine learning: https://github.com/dair-ai/ML-Papers-Explained

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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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Repost from Machine Learning
Uniface Automate face detection, recognition, and analysis of key facial landmarks with the Uniface Python library. https://g
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