Machine Learning with Python
الذهاب إلى القناة على Telegram
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
إظهار المزيد
الشبكة:📈 نظرة تحليلية على قناة تيليجرام Machine Learning with Python
تُعد قناة Machine Learning with Python (@codeprogrammer) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 68 536 مشتركاً، محتلاً المرتبة 2 402 في فئة التعليم والمرتبة 4 600 في منطقة الهند.
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منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 68 536 مشتركاً.
بحسب آخر البيانات بتاريخ 29 أكتوبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 74، وفي آخر 24 ساعة بمقدار -5، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 3.84%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.47% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 2 629 مشاهدة. وخلال اليوم الأول يجمع عادةً 1 007 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 9.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل insidead, learning, degree, evaluation, algorithm.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 30 أكتوبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.
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😎 Machine Learning Cheatsheet — a structured ML guide!
There are no courses here, no unnecessary theory or long lectures, but there are clear formulas, algorithms, the logic of ML pipelines, and a neatly structured knowledge base. It's perfect for quickly refreshing your understanding of algorithms or having it handy as an ML cheat sheet during work.
📌 Here's the link: ml-cheatsheet.readthedocs.io
🚪 @codeprogrammer | #resource
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Repost from ADMINOTEKA
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Collection of books on machine learning and artificial intelligence in PDF format
Repo: https://github.com/Ramakm/AI-ML-Book-References
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👉 @codeprogrammer
Repost from Machine Learning with Python
🤖 Machine Learning Tutorials Repository
1. Python
2. Computer Vision: Techniques, algorithms
3. NLP
4. Matplotlib
5. NumPy
6. Pandas
7. MLOps
8. LLMs
9. PyTorch/TensorFlow
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YOLO Training Template
Manual data labeling has become significantly more convenient. Now the process looks like in the usual labeling systems - you just outline the object with a frame and a bounding box is immediately created.
The platform allows:
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0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
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8️⃣ programming Languages
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