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AI and Machine Learning

AI and Machine Learning

الذهاب إلى القناة على Telegram

Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses

إظهار المزيد

📈 نظرة تحليلية على قناة تيليجرام AI and Machine Learning

تُعد قناة AI and Machine Learning (@machine_learning_courses) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 94 085 مشتركاً، محتلاً المرتبة 1 556 في فئة التعليم والمرتبة 3 013 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 94 085 مشتركاً.

بحسب آخر البيانات بتاريخ 25 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 981، وفي آخر 24 ساعة بمقدار 47، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 6.77‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 2.34‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 6 370 مشاهدة. وخلال اليوم الأول يجمع عادةً 2 203 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 9.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل learning, llm, linkedin, linux, udemy.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 26 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

94 085
المشتركون
+4724 ساعات
+1877 أيام
+98130 أيام
أرشيف المشاركات
07 - Appendix - Python Crash Course

06 - Deploying in another open-course cloud

05 - Deploy Web App in Heroku Cloud

04 - Face Recognition Project (Integrating HTML Model to Flask App)

03 - Develop Face Recognition Model with Machine Learning from Scratch - Part 04

03 - Develop Face Recognition Model with Machine Learning from Scratch - Part 03

03 - Develop Face Recognition Model with Machine Learning from Scratch - Part 02

03 - Develop Face Recognition Model with Machine Learning from Scratch - Part 01

02 - Image Processing with OpenCV

01 - Introduction - Part 02

01 - Introduction - Part 01

🧠 Face Recognition with Machine Learning + Deploy Flask App 🌟 4.4 - 459 votes 💰 Original Price: $69.99 📖 Create an Face R
🧠 Face Recognition with Machine Learning + Deploy Flask App 🌟 4.4 - 459 votes 💰 Original Price: $69.99
📖 Create an Face Recognition project from scratch with Python, OpenCV , Machine Learning Algorithms, Flask, Heroku Deploy
🔊 Taught By: datascience Anywhere, G Sudheer 📤 Download Full Course 📤 Download All Courses

💰 AI Terms You Must Know
💰 AI Terms You Must Know

⚠️ Exciting News! 🎉 Thanks to your votes and support, we’re thrilled to announce the launch of our new channel: The Coding S
⚠️ Exciting News! 🎉 Thanks to your votes and support, we’re thrilled to announce the launch of our new channel: The Coding Space!
This channel is dedicated to helping you master programming and coding, featuring tutorials on Python, Java, C, C++, C#, and more. Whether you’re a beginner or looking to level up your skills, The Coding Space is here to guide you.
🌟 Stay tuned for high-quality content, tips, and resources designed to make you a better programmer! 📱 Join us now and start coding smarter! Thank you for being an amazing community! ❤️

AI is learning very fast.

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📦 Exercise Files

📱Machine Learning and Artificial intelligence 📱Machine Learning and AI Foundations: Advanced Decision Trees with KNIME

🔅 Machine Learning and AI Foundations: Advanced Decision Trees with KNIME 🌐 Author: Keith McCormick 🔰 Level: Advanced ⏰ Du
🔅 Machine Learning and AI Foundations: Advanced Decision Trees with KNIME 🌐 Author: Keith McCormick 🔰 Level: AdvancedDuration: 1h 33m
🌀 Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.
📗 Topics: Decision Trees, Knime, Machine Learning 📤 Join Machine Learning and Artificial intelligence for more courses