Machine Learning

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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

إظهار المزيد

الشبكة:Machine Learning with Python سوريا232 التكنولوجيات والتطبيقات3 398...

📈 نظرة تحليلية على قناة تيليجرام Machine Learning

تُعد قناة Machine Learning (@machinelearning9) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 40 100 مشتركاً، محتلاً المرتبة 3 398 في فئة التكنولوجيات والتطبيقات والمرتبة 232 في منطقة سوريا.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 40 100 مشتركاً.

بحسب آخر البيانات بتاريخ 23 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 379، وفي آخر 24 ساعة بمقدار 30، مع بقاء الوصول العام مرتفعاً.

حالة التحقق: غير موثّقة
معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 1.92‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.16‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
وصول المنشورات: يحصل كل منشور على متوسط 770 مشاهدة. وخلال اليوم الأول يجمع عادةً 466 مشاهدة.
التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 3.
الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل distance, insidead, gpu, learning, degree.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 24 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

40 100

المشتركون

+3024 ساعات

+337 أيام

+37930 أيام

770

عرض المشاهدات

~ 46624 ساعات

~ 62048 ساعات

1.92%

معدل المشاركة

~ 3

المشاركات في اليوم

Ads index

beta

أرشيف المشاركات

40 105

📌 The Proximity of the Inception Score as an Evaluation Criterion 🗂 Category: DEEP LEARNING 🕒 Date: 2026-02-03 | ⏱️ Read time: 7 min read The neighborhood of synthetic data #DataScience #AI #Python

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📌 Building Systems That Survive Real Life 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2026-02-02 | ⏱️ Read time: 4 min read Sara Nobrega on the transition from data science to AI engineering, using LLMs as a… #DataScience #AI #Python

40 105

📌 Silicon Darwinism: Why Scarcity Is the Source of True Intelligence 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-02 | ⏱️ Read time: 9 min read We are confusing “size” with “smart.” The next leap in artificial intelligence will not come… #DataScience #AI #Python

40 105

📌 Distributed Reinforcement Learning for Scalable High-Performance Policy Optimization 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-02-01 | ⏱️ Read time: 20 min read Leveraging massive parallelism, asynchronous updates, and multi-machine training to match and exceed human-level performance #DataScience #AI #Python

40 105

📌 How to Apply Agentic Coding to Solve Problems 🗂 Category: AGENTIC AI 🕒 Date: 2026-01-31 | ⏱️ Read time: 7 min read Learn how to efficiently solve problems with coding agents #DataScience #AI #Python

40 105

📌 How to Run Claude Code for Free with Local and Cloud Models from Ollama 🗂 Category: PROGRAMMING 🕒 Date: 2026-01-31 | ⏱️ Read time: 16 min read Ollama now offers Anthropic API compatibility #DataScience #AI #Python

40 105

📌 Multi-Attribute Decision Matrices, Done Right 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-30 | ⏱️ Read time: 7 min read How to structure decisions, identify efficient options, and avoid misleading value metrics #DataScience #AI #Python

40 105

📌 On the Possibility of Small Networks for Physics-Informed Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-30 | ⏱️ Read time: 20 min read A new kind of hyperparameter study #DataScience #AI #Python

40 105

📌 Why Your Multi-Agent System is Failing: Escaping the 17x Error Trap of the “Bag of Agents” 🗂 Category: AGENTIC AI 🕒 Date: 2026-01-30 | ⏱️ Read time: 27 min read Hard-won lessons on how to scale agentic systems without scaling the chaos, including a taxonomy… #DataScience #AI #Python

40 105

📌 Creating an Etch A Sketch App Using Python and Turtle 🗂 Category: PROGRAMMING 🕒 Date: 2026-01-30 | ⏱️ Read time: 7 min read A beginner-friendly Python tutorial #DataScience #AI #Python

40 105

📌 Randomization Works in Experiments, Even Without Balance 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-29 | ⏱️ Read time: 10 min read Randomization usually balances confounders in experiments, but what happens when it doesn’t? #DataScience #AI #Python

40 105

📌 The Unbearable Lightness of Coding 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-01-29 | ⏱️ Read time: 9 min read Confessions of a vibe coder #DataScience #AI #Python

40 105

📌 RoPE, Clearly Explained 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-29 | ⏱️ Read time: 8 min read Going beyond the math to build intuition #DataScience #AI #Python

40 105

📌 Optimizing Vector Search: Why You Should Flatten Structured Data 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-29 | ⏱️ Read time: 7 min read An analysis of how flattening structured data can boost precision and recall by up to 20% #DataScience #AI #Python

40 105

📌 Machine Learning in Production? What This Really Means 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-28 | ⏱️ Read time: 10 min read From notebooks to real-world systems #DataScience #AI #Python

40 105

📌 Federated Learning, Part 2: Implementation with the Flower Framework 🗂 Category: FEDERATED LEARNING 🕒 Date: 2026-01-28 | ⏱️ Read time: 11 min read Implementing cross-silo federated learning step by step #DataScience #AI #Python

40 105

📌 Modeling Urban Walking Risk Using Spatial-Temporal Machine Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-28 | ⏱️ Read time: 12 min read Estimating neighborhood-level pedestrian risk from real-world incident data #DataScience #AI #Python

40 105

📌 I Ditched My Mouse: How I Control My Computer With Hand Gestures (In 60 Lines of Python) 🗂 Category: COMPUTER VISION 🕒 Date: 2026-01-28 | ⏱️ Read time: 9 min read A step-by-step guide to building a “Minority Report”-style interface using OpenCV and MediaPipe #DataScience #AI #Python

40 105

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40 105

Repost from Machine Learning with Python

💛 Top 10 Best Websites to Learn Machine Learning ⭐️ by [@codeprogrammer] --- 🧠 Google’s ML Course 🔗 https://developers.google.com/machine-learning/crash-course 📈 Kaggle Courses 🔗 https://kaggle.com/learn 🧑‍🎓 Coursera – Andrew Ng’s ML Course 🔗 https://coursera.org/learn/machine-learning ⚡️ Fast.ai 🔗 https://fast.ai 🔧 Scikit-Learn Documentation 🔗 https://scikit-learn.org 📹 TensorFlow Tutorials 🔗 https://tensorflow.org/tutorials 🔥 PyTorch Tutorials 🔗 https://docs.pytorch.org/tutorials/ 🏛️ MIT OpenCourseWare – Machine Learning 🔗 https://ocw.mit.edu/courses/6-867-machine-learning-fall-2006/ ✍️ Towards Data Science (Blog) 🔗 https://towardsdatascience.com --- 💡 Which one are you starting with? Drop a comment below! 👇 #MachineLearning #LearnML #DataScience #AI https://t.me/CodeProgrammer 🌟