متاح الآن! بحث تيليغرام 2025 — أهم رؤى العام 
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📈 نظرة تحليلية على قناة تيليجرام Machine Learning
تُعد قناة Machine Learning (@machinelearning9) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 40 151 مشتركاً، محتلاً المرتبة 3 380 في فئة التكنولوجيات والتطبيقات والمرتبة 228 في منطقة سوريا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 40 151 مشتركاً.
بحسب آخر البيانات بتاريخ 29 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 380، وفي آخر 24 ساعة بمقدار 3، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 2.08%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.91% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 837 مشاهدة. وخلال اليوم الأول يجمع عادةً 766 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 30 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
40 151
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40 162
📌 The Best Data Scientists are Always Learning
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-04 | ⏱️ Read time: 7 min read
Why continuous learning matters & how to come up with topics to study
#DataScience #AI #Python
40 162
📌 Bootstrap a Data Lakehouse in an Afternoon
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-12-04 | ⏱️ Read time: 12 min read
Using Apache Iceberg on AWS with Athena, Glue/Spark and DuckDB
#DataScience #AI #Python
40 162
📌 Build and Deploy Your First Supply Chain App in 20 Minutes
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-04 | ⏱️ Read time: 21 min read
A factory operator that discovered happiness by switching from notebook to streamlit – (Image Generated…
#DataScience #AI #Python
40 162
📌 The Machine Learning “Advent Calendar” Day 4: k-Means in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-04 | ⏱️ Read time: 7 min read
Discover how to implement the k-Means clustering algorithm, a fundamental machine learning technique, using only Microsoft Excel. This guide, part of a "Machine Learning Advent Calendar" series, walks through building a training algorithm from scratch in a familiar spreadsheet environment, demystifying what "real" ML looks like in practice.
#MachineLearning #kMeans #Excel #DataScience #Tutorial
40 162
📌 Do Labels Make AI Blind? Self-Supervision Solves the Age-Old Binding Problem
🗂 Category: DEEP LEARNING
🕒 Date: 2025-12-04 | ⏱️ Read time: 16 min read
A new NeurIPS 2025 paper suggests that traditional labels may hinder an AI's holistic image understanding, a challenge known as the "binding problem." Research shows that self-supervised learning methods can overcome this, significantly improving the capabilities of Vision Transformers (ViT) by allowing them to better integrate various visual features without explicit labels. This breakthrough points to a future where models learn more like humans, leading to more robust and nuanced computer vision.
#AI #SelfSupervisedLearning #ComputerVision #ViT
40 162
📌 On the Challenge of Converting TensorFlow Models to PyTorch
🗂 Category: DEEP LEARNING
🕒 Date: 2025-12-05 | ⏱️ Read time: 19 min read
Converting legacy TensorFlow models to PyTorch presents significant challenges but offers opportunities for modernization and optimization. This guide explores the common hurdles in the migration process, from architectural differences to API incompatibilities, and provides practical strategies for successfully upgrading your AI/ML pipelines. Learn how to not only convert but also enhance your models for better performance and maintainability in the PyTorch ecosystem.
#PyTorch #TensorFlow #ModelConversion #MLOps #DeepLearning
40 162
📌 YOLOv1 Paper Walkthrough: The Day YOLO First Saw the World
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-12-05 | ⏱️ Read time: 17 min read
A deep dive into the original YOLOv1 paper, exploring the revolutionary "You Only Look Once" algorithm. This technical walkthrough breaks down the foundational object detection architecture and guides readers through a complete implementation from scratch using PyTorch. It's an essential resource for understanding the core mechanics of single-shot detectors and the history of computer vision.
#YOLO #ObjectDetection #ComputerVision #PyTorch
40 162
📌 A Product Data Scientist’s Take on LinkedIn Games After 500 Days of Play
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-05 | ⏱️ Read time: 14 min read
A product data scientist offers a unique analysis of LinkedIn's puzzle games after 500 consecutive days of play. The article delves into key takeaways on user engagement, experimentation, and data-driven product thinking, revealing how observing a simple game can provide valuable lessons for complex product strategy and development in the tech industry.
#DataScience #ProductManagement #UserEngagement #Experimentation
40 162
📌 The Machine Learning “Advent Calendar” Day 5: GMM in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-05 | ⏱️ Read time: 6 min read
Explore Gaussian Mixture Models (GMM), a powerful clustering algorithm that serves as a natural extension and improvement over k-Means. This guide, part of a Machine Learning Advent Calendar series, uniquely demonstrates how to implement and understand GMMs entirely within Microsoft Excel. It's a practical approach for grasping core ML concepts without requiring a dedicated coding environment, making advanced data science techniques more accessible.
#MachineLearning #GMM #Excel #DataScience #Clustering
40 162
📌 The Step-by-Step Process of Adding a New Feature to My IOS App with Cursor
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-12-05 | ⏱️ Read time: 6 min read
This article provides a step-by-step walkthrough of adding a new feature to an iOS app using the AI-powered editor, Cursor. It offers practical insights for developers, highlighting how Cursor excels at code generation but is less effective for UI/UX design tasks. This guide demonstrates a real-world workflow for integrating AI coding assistants into the development process, showcasing both their strengths and limitations.
#iOSDev #AICoding #AppDevelopment #Cursor
40 162
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
40 162
📌 How to Use Simple Data Contracts in Python for Data Scientists
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-02 | ⏱️ Read time: 5 min read
Prevent your data pipelines from breaking unexpectedly. This article demonstrates how to implement simple data contracts in Python using Pandera, an open-source validation library. Learn to define and enforce data quality rules to build more robust and reliable data science workflows, ensuring your data meets expectations before it causes issues downstream.
#DataContracts #Python #DataScience #Pandera #DataValidation
40 162
📌 How to Code Your Own Website with AI
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-03 | ⏱️ Read time: 8 min read
Unlock the potential of AI in web development. This guide explains how to "vibe-code" a website, a modern method where AI tools translate your high-level design concepts and desired feel directly into functional code. Learn a more intuitive and streamlined approach to building websites from scratch.
#AI #WebDevelopment #AICoding #DeveloperTools #GenerativeAI
40 162
📌 Multi-Agent Arena: Insights from London Great Agent Hack 2025
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-03 | ⏱️ Read time: 16 min read
Key insights from the London Great Agent Hack 2025 reveal critical success factors for multi-agent systems. The focus has shifted towards building highly robust agents capable of withstanding adversarial testing and unexpected scenarios. A major theme was the importance of "glass-box reasoning"—making agent decision-making transparent and interpretable. Ultimately, red-team resilience and explainability, not just raw performance, were the defining characteristics of the top-performing solutions.
#MultiAgentSystems #AIAgents #ExplainableAI #AISecurity
40 162
📌 How to Turn Your LLM Prototype into a Production-Ready System
🗂 Category: LLM APPLICATIONS
🕒 Date: 2025-12-03 | ⏱️ Read time: 15 min read
Transforming a promising LLM prototype into a production-ready system involves significant engineering challenges. This guide outlines the essential steps and best practices for moving beyond the experimental phase, focusing on building scalable, reliable, and efficient LLM applications for real-world deployment. Learn how to successfully operationalize your language model from concept to production.
#LLM #MLOps #ProductionAI #LLMOps
40 162
📌 The Machine Learning “Advent Calendar” Day 3: GNB, LDA and QDA in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-03 | ⏱️ Read time: 10 min read
Day 3 of the Machine Learning "Advent Calendar" series explores Gaussian Naive Bayes (GNB), Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis (QDA). This guide uniquely demonstrates how to implement these powerful classification algorithms directly within Excel, offering a practical, code-free approach. Learn the core concepts behind these models, transitioning from simple local distance metrics to a more robust global probability framework, making advanced statistical methods accessible to a wider audience.
#MachineLearning #Excel #DataScience #LDA #Statistics
40 162
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40 162
📌 Overcoming the Hidden Performance Traps of Variable-Shaped Tensors: Efficient Data Sampling in PyTorch
🗂 Category: DEEP LEARNING
🕒 Date: 2025-12-03 | ⏱️ Read time: 10 min read
Unlock peak PyTorch performance by addressing the hidden bottlenecks caused by variable-shaped tensors. This deep dive focuses on the critical data sampling phase, offering practical optimization strategies to handle tensors of varying sizes efficiently. Learn how to analyze and improve your data loading pipeline for faster model training and overall performance gains.
#PyTorch #PerformanceOptimization #DeepLearning #MLOps
40 162
📌 The Architecture Behind Web Search in AI Chatbots
🗂 Category: LLM APPLICATIONS
🕒 Date: 2025-12-04 | ⏱️ Read time: 16 min read
Explore the technical architecture powering web search in AI chatbots. This analysis breaks down how generative models retrieve and integrate live web data to provide current answers, highlighting the crucial shift towards Generative Engine Optimization (GEO). Learn what this new paradigm means for content visibility in an AI-first search landscape, moving beyond traditional SEO.
#AI #GEO #Chatbots #Search #RAG
