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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 67 809 підписників, посідаючи 2 416 місце в категорії Освіта та 5 038 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 67 809 підписників.

За останніми даними від 09 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 70, а за останні 24 години на 10, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 2.94%. Протягом перших 24 годин після публікації контент зазвичай збирає 2.44% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 1 997 переглядів. Протягом першої доби публікація в середньому набирає 1 652 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 7.
  • 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 10 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.

67 809
Підписники
+1024 години
+127 днів
+7030 день
Архів дописів
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This repository contains a collection of everything needed to work with libraries related to AI and LLM. More than 120 libraries, sorted by stages of LLM development: → Training, fine-tuning, and evaluation of LLM models → Integration and deployment of applications with LLM and RAG → Fast and scalable model launching → Working with data: extraction, structuring, and synthetic generation → Creating autonomous agents based on LLM → Prompt optimization and ensuring safe use in production 🌟 link: https://github.com/Shubhamsaboo/awesome-llm-apps 👉 @codeprogrammer

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