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

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

📌 Achieving 5x Agentic Coding Performance with Few-Shot Prompting 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-23 | ⏱️ Read time: 9 min read Learn to leverage few-shot prompting to increase your LLMs performance #DataScience #AI #Python

40 105

📌 Optimizing Data Transfer in Distributed AI/ML Training Workloads 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-01-23 | ⏱️ Read time: 15 min read A deep dive on data transfer bottlenecks, their identification, and their resolution with the help… #DataScience #AI #Python

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📌 What Other Industries Can Learn from Healthcare’s Knowledge Graphs 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-22 | ⏱️ Read time: 11 min read How shared meaning, evidence, and standards create durable semantic infrastructure #DataScience #AI #Python

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📌 Stop Writing Messy Boolean Masks: 10 Elegant Ways to Filter Pandas DataFrames 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-22 | ⏱️ Read time: 7 min read Master the art of readable, high-performance data selection using .query(), .isin(), and advanced vectorized logic. #DataScience #AI #Python

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📌 Why SaaS Product Management Is the Best Domain for Data-Driven Professionals in 2026 🗂 Category: PRODUCT MANAGEMENT 🕒 Date: 2026-01-22 | ⏱️ Read time: 14 min read How I use analytics, automation, and AI to build better SaaS #DataScience #AI #Python

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📌 Evaluating Multi-Step LLM-Generated Content: Why Customer Journeys Require Structural Metrics 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-22 | ⏱️ Read time: 13 min read How to evaluate goal-oriented content designed to build engagement and deliver business results, and why… #DataScience #AI #Python

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📌 A Case for the T-statistic 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-21 | ⏱️ Read time: 21 min read And how it compares to the run-of-the-mill z-score #DataScience #AI #Python

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Guide to AI Coding Agents & Assistants: How to Choose the Right One There are now so many AI tools for coding that it can be confusing to know which one to pick. Some act as simple helpers (Assistant), while others can do the work for you (Agent). This guide breaks down the top AI coding tools that you should be aware of. We will look at what they do, who they are for, and how much they cost. Read: https://habr.com/en/articles/979402/ https://t.me/DataScienceM

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📌 Building a Self-Healing Data Pipeline That Fixes Its Own Python Errors 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-01-21 | ⏱️ Read time: 8 min read How I built a self-healing pipeline that automatically fixes bad CSVs, schema changes, and weird… #DataScience #AI #Python

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📌 If You Want to Become a Data Scientist in 2026, Do This 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-21 | ⏱️ Read time: 10 min read Learn from my mistakes and fast track your data science career #DataScience #AI #Python

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📌 Google Trends is Misleading You: How to Do Machine Learning with Google Trends Data 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-21 | ⏱️ Read time: 11 min read Google Trends is one of the most widely used tools for analysing human behaviour at… #DataScience #AI #Python

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📌 How to Perform Large Code Refactors in Cursor 🗂 Category: AGENTIC AI 🕒 Date: 2026-01-20 | ⏱️ Read time: 10 min read Learn how to perform code refactoring with LLMs #DataScience #AI #Python

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📌 Does Calendar-Based Time-Intelligence Change Custom Logic? 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-20 | ⏱️ Read time: 8 min read Let’s look at calculating the moving average over time #DataScience #AI #Python

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📌 Why Package Installs Are Slow (And How to Fix It) 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-01-20 | ⏱️ Read time: 7 min read How sharded indexing patterns solve a scaling problem in package management #DataScience #AI #Python

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📌 You Probably Don’t Need a Vector Database for Your RAG — Yet 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-20 | ⏱️ Read time: 14 min read Numpy or SciKit-Learn might meet all your retrieval needs #DataScience #AI #Python

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📌 Bridging the Gap Between Research and Readability with Marco Hening Tallarico 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2026-01-19 | ⏱️ Read time: 6 min read Diluting complex research, spotting silent data leaks, and why the best way to learn is… #DataScience #AI #Python