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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 68 102 підписників, посідаючи 2 372 місце в категорії Освіта та 4 808 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 68 102 підписників.

За останніми даними від 27 серпня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 112, а за останні 24 години на 8, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 4.52%. Протягом перших 24 годин після публікації контент зазвичай збирає 1.90% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 3 077 переглядів. Протягом першої доби публікація в середньому набирає 1 291 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 5.
  • 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 28 серпня, 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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68 102
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+11230 день
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ТехноHub — твій гід у світі технологій, IT‑індустрії та цифрових інновацій. Підписуйся, щоб бути в курсі: https://t.me/hubtech_ua

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Design patterns are proven solutions to common problems in development. If you've ever found yourself constantly writing the
Design patterns are proven solutions to common problems in development. If you've ever found yourself constantly writing the same thing when creating objects or struggling with managing different types of objects, then the factory pattern might be exactly what you need. In this tutorial: https://www.freecodecamp.org/news/how-to-use-the-factory-pattern-in-python-a-practical-guide/ you'll learn what a factory is, why it's useful, and how to implement it in #Python. We'll gather practical examples that will show when and how to apply this pattern in real tasks. The code can be found on #GitHub https://github.com/balapriyac/python-basics/tree/main/design-patterns/factory https://t.me/CodeProgrammer

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These 9 lectures from Stanford are a pure goldmine for anyone wanting to learn and understand LLMs in depth Lecture 1 - Trans
These 9 lectures from Stanford are a pure goldmine for anyone wanting to learn and understand LLMs in depth Lecture 1 - Transformer: https://lnkd.in/dGnQW39t Lecture 2 - Transformer-Based Models & Tricks: https://lnkd.in/dT_VEpVH Lecture 3 - Tranformers & Large Language Models: https://lnkd.in/dwjjpjaP Lecture 4 - LLM Training: https://lnkd.in/dSi_xCEN Lecture 5 - LLM tuning: https://lnkd.in/dUK5djpB Lecture 6 - LLM Reasoning: https://lnkd.in/dAGQTNAM Lecture 7 - Agentic LLMs: https://lnkd.in/dWD4j7vm Lecture 8 - LLM Evaluation: https://lnkd.in/ddxE5zvb Lecture 9 - Recap & Current Trends: https://lnkd.in/dGsTd8jN Start understanding #LLMs in depth from the experts. Go through each step-by-step video. https://t.me/DataAnalyticsX 🔗

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