متاح الآن! بحث تيليغرام 2025 — أهم رؤى العام 
Machine Learning
الذهاب إلى القناة على Telegram
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📈 نظرة تحليلية على قناة تيليجرام Machine Learning
تُعد قناة Machine Learning (@machinelearning9) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 40 040 مشتركاً، محتلاً المرتبة 3 406 في فئة التكنولوجيات والتطبيقات والمرتبة 232 في منطقة سوريا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 40 040 مشتركاً.
بحسب آخر البيانات بتاريخ 22 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 372، وفي آخر 24 ساعة بمقدار 2، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 1.94%. 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 775 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 23 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
40 040
المشتركون
+224 ساعات
+237 أيام
+37230 أيام
أرشيف المشاركات
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📌 A Career in Data Is Not Always a Straight Line, and That’s Okay
🗂 Category: AUTHOR SPOTLIGHTS
🕒 Date: 2026-04-27 | ⏱️ Read time: 9 min read
Sabrine Bendimerad on why flexibility is a crucial data science skill, the risks of outsourcing…
#DataScience #AI #Python
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📌 Comparing Explicit Measures to Calculation Groups in Tabular Models
🗂 Category: DATA MODELING
🕒 Date: 2026-04-27 | ⏱️ Read time: 6 min read
With the advent of UDFs and their combination with calculation groups, I see a lot…
#DataScience #AI #Python
40 040
📌 How Spreadsheets Quietly Cost Supply Chains Millions
🗂 Category: PRODUCT MANAGEMENT
🕒 Date: 2026-04-27 | ⏱️ Read time: 14 min read
A simulation of how a single forecast change moves through five planning teams, and why…
#DataScience #AI #Python
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CVE | Cyber Vulnerabilities Exchange
Group dedicated to sharing and discussing CVEs, zero-days, critical vulnerabilities, exploits, PoCs, and technical analyses of offensive and defensive security.
What you'll find here:
• Newly disclosed CVEs
• Public and private exploits
• Technical analysis and bypasses
• Offensive/defensive security
• Penetration testing and red team discussions
Technical, direct, and straightforward content.
Channel=> https://t.me/cve0day
Think. Break. Secure.
40 040
📌 I Reduced My Pandas Runtime by 95% — Here’s What I Was Doing Wrong
🗂 Category: PROGRAMMING
🕒 Date: 2026-04-26 | ⏱️ Read time: 18 min read
Most slow Pandas code “works”, until it doesn’t. Learn how to spot hidden bottlenecks, avoid…
#DataScience #AI #Python
40 040
📌 Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning
🗂 Category: DEEP LEARNING
🕒 Date: 2026-04-26 | ⏱️ Read time: 12 min read
Why learn 8 scripts when you can learn 256 bytes?
#DataScience #AI #Python
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Repost from Machine Learning with Python
GitHub repositories to enhance your Python proficiency:
- Web development with Django — https://github.com/django/django
- Data Science tools — https://github.com/rasbt/python-machine-learning-book
- Algorithmic challenges — https://github.com/TheAlgorithms/Python
- Machine learning recipes — https://github.com/ageron/handson-ml2
- Testing best practices — https://github.com/pytest-dev/pytest
- Automation scripts — https://github.com/soimort/you-get
- Advanced Python concepts — https://github.com/faif/python-patterns
Bookmark and share
https://t.me/CodeProgrammer 🌟
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Repost from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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📌 The Essential Guide to Effectively Summarizing Massive Documents, Part 2
🗂 Category: LLM APPLICATIONS
🕒 Date: 2026-04-25 | ⏱️ Read time: 18 min read
We have the document clusters, and it’s time to unlock their true potential! Let’s explore…
#DataScience #AI #Python
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📌 Causal Inference Is Different in Business
🗂 Category: DATA SCIENCE
🕒 Date: 2026-04-25 | ⏱️ Read time: 12 min read
How does decision-gravity dictate this gap?
#DataScience #AI #Python
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Headline: USA vs. IRAN: The Real Story
Three US aircraft carriers are now in the Middle East. Diplomacy is at a breaking point in Islamabad. Are we on the verge of an "everlasting agreement" or total escalation?
Alex Barnicoat News provides the critical breakdown of the 2026 conflict:
Military Analysis: Deep dives into US weaponry and Iranian naval tactics.
Geopolitical Impact: How the blockade is reshaping global trade.
Daily Video News: Quick, hard-hitting updates on "Actually Important News."
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📌 How to Select Variables Robustly in a Scoring Model
🗂 Category: DATA SCIENCE
🕒 Date: 2026-04-24 | ⏱️ Read time: 7 min read
More variables don’t make a better scoring model. Stable variables do. Here’s how to find them.
#DataScience #AI #Python
40 040
📌 How to Improve Claude Code Performance with Automated Testing
🗂 Category: AGENTIC AI
🕒 Date: 2026-04-24 | ⏱️ Read time: 10 min read
Learn how to get the most out of Claude Code
#DataScience #AI #Python
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📌 I Built an AI Pipeline for Kindle Highlights
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2026-04-24 | ⏱️ Read time: 12 min read
A local, zero-cost project that cleans, structures, and summarizes your reading automatically
#DataScience #AI #Python
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📌 Introduction to Approximate Solution Methods for Reinforcement Learning
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-04-24 | ⏱️ Read time: 9 min read
Learn about function approximation and the different choices for approximation functions
#DataScience #AI #Python
