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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
Больше📈 Аналитический обзор Telegram-канала Machine Learning with Python
Канал Machine Learning with Python (@codeprogrammer) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 67 813 подписчиков, занимая 2 427 место в категории Образование и 5 028 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 67 813 подписчиков.
Согласно последним данным от 13 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 60, а за последние 24 часа — -3, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 4.31%. В первые 24 часа после публикации контент обычно набирает 1.69% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 926 просмотров. В течение первых суток публикация набирает 1 148 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 6.
- 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 14 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.
67 813
Подписчики
-324 часа
-77 дней
+6030 день
Архив постов
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Repost from Machine Learning
Are you fluent in Python and want to evaluate your skills? 🤔
Do you want to learn Python? 🤗
Are you interested in learning through questions and answers? 😵
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✅ Learn PyTorch in 4 steps
👨🏻💻 With support for more than 200 different mathematical operations, PyTorch is one of the most powerful open source and computational libraries based on Python for machine learning. You don't need to look for different sources to learn this popular library, but the website of this library covers more than what you need.💯
2️⃣ Here, I will teach you how to learn PyTorch from scratch in 4 steps. 👌🏼
1️⃣ Text tutorial: If you don't know anything about Python, you should start learning from here.
⬅️ Topics: tensors, datasets and DataLoader, model building, optimization loop, saving, loading and using the model.
📄 PyTorch Basics
┘📎 Link: Learn the Basics
2️⃣ Video training: This section is very useful for those who prefer video content.
⬅️ Topics: introduction, tensor construction and model construction with pytorch.
📄 Introduction to PyTorch
┘📎 Link: Introduction to PyTorch
3️⃣ Examining examples: By viewing different examples, you will review what you have learned so far.
📄 Learning Python by example
┘📎 Link: Learning PyTorch with Examples
4️⃣ Coding: This step is vital! Your theoretical knowledge is worthless without coding! The Keras website is full of sample code that is great for getting started.
📄 Start coding
┘📎 Link: keras.io
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
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7️⃣ Deep Learning
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Repost from Python Courses & Resources
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🔥 Large selection of interview questions on DS, AI, ML, DL, NLP, computer vision . Part 2
✅ Machine learning interview questions and answers for data scientists
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✅ Questions and answers to interviews on computer vision part 1
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✅ Questions and answers to computer vision interviews part 3
