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

Network:Machine Learning with Python Syria231 Technologies & Applications3 380...

📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 134 subscribers, ranking 3 380 in the Technologies & Applications category and 231 in the Syria region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 134 subscribers.

According to the latest data from 25 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 395 over the last 30 days and by 12 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 1.89%. Within the first 24 hours after publication, content typically collects 1.31% reactions from the total number of subscribers.
Post reach: On average, each post receives 758 views. Within the first day, a publication typically gains 525 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
Thematic interests: Content is focused on key topics such as distance, insidead, gpu, learning, degree.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 26 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

40 134

Subscribers

+1224 hours

+697 days

+39530 days

758

Post views

~ 52524 hours

~ 70348 hours

1.89%

Engagement rate

~ 3

Posts per day

Ads index

beta

Posts Archive

40 138

📌 TDS Newsletter: November Must-Reads on GraphRAG, ML Projects, LLM-Powered Time-Series Analysis, and More 🗂 Category: THE VARIABLE 🕒 Date: 2025-11-27 | ⏱️ Read time: 3 min read Towards Data Science's November newsletter highlights the month's most popular articles for the tech community. Key topics include the innovative GraphRAG technique for enhancing language models, practical guidance for structuring successful machine learning projects, and the application of LLMs for advanced time-series analysis. This roundup offers essential insights into the latest trends and developments in the field. #GraphRAG #LLM #MachineLearning #DataScience #TimeSeries

40 138

📌 The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation 🗂 Category: PRODUCT MANAGEMENT 🕒 Date: 2025-11-28 | ⏱️ Read time: 10 min read Discover how a unified Product Health Score, powered by integrated monitoring and n8n automation, can align product, growth, and engineering teams. This single-signal approach streamlines incident management and successfully reduced critical incidents by an impressive 35%, creating a more stable and reliable product. #ProductHealth #Automation #n8n #IncidentManagement #DevOps

40 138

📌 Why We’ve Been Optimizing the Wrong Thing in LLMs for Years 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-11-28 | ⏱️ Read time: 14 min read LLM development may have been focused on the wrong optimization targets for years. A new analysis reveals that a simple shift in the training process is the key to unlocking significant improvements. This approach reportedly leads to models with enhanced foresight, faster inference speeds, and substantially better reasoning abilities, challenging conventional development practices. #LLM #AITraining #ModelOptimization #AI #Inference

40 138

📌 Data Science in 2026: Is It Still Worth It? 🗂 Category: DATA SCIENCE 🕒 Date: 2025-11-28 | ⏱️ Read time: 9 min read Is data science still a viable career path by 2026? A veteran AI engineer with a decade of experience offers a candid perspective on the evolution of the field. This piece explores the future demand for data scientists, the impact of automation and advanced AI on the role, and whether it's still worth pursuing for aspiring and current professionals. #DataScience #AI #TechCareer #FutureOfWork

40 138

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40 138

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40 138

📌 Implementing the Rock Paper Scissors Game in Python 🗂 Category: PROGRAMMING 🕒 Date: 2025-11-27 | ⏱️ Read time: 4 min read Master Python basics by building a classic Rock Paper Scissors game. This beginner-friendly tutorial demonstrates how to use the random module for the computer's choice and apply conditional logic to determine the winner. It is a perfect hands-on project for new developers to practice fundamental programming concepts. #Python #PythonForBeginners #PythonProject #CodingTutorial

40 138

📌 Everyday Decisions are Noisier Than You Think — Here’s How AI Can Help Fix That 🗂 Category: DATA SCIENCE 🕒 Date: 2025-11-27 | ⏱️ Read time: 24 min read Inconsistency in human judgment, or "noise," creates significant problems in fields ranging from insurance to justice. This hidden flaw leads to unpredictable and often unfair outcomes. AI presents a powerful solution by introducing data-driven consistency, helping to reduce this variability and improve the quality and fairness of critical decisions. By standardizing processes where consistency is paramount, AI can lead to more reliable and equitable results across various sectors. #AI #DecisionMaking #NoiseReduction #DataScience

40 138

📌 Water Cooler Small Talk, Ep. 10: So, What About the AI Bubble? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-11-27 | ⏱️ Read time: 10 min read The tech world is buzzing with AI advancements, but is it a sustainable boom or a bubble on the verge of popping? This discussion explores the massive investments and lofty promises fueling the current AI hype, critically examining whether we're being sold an impossibly expensive and unrealistic future. #AIBubble #ArtificialIntelligence #TechTrends #FutureOfAI

40 138

📌 Neural Networks Are Blurry, Symbolic Systems Are Fragmented. Sparse Autoencoders Help Us Combine Them. 🗂 Category: DEEP LEARNING 🕒 Date: 2025-11-27 | ⏱️ Read time: 17 min read Neural networks and symbolic AI models compress information in fundamentally different ways, leading to "blurry" continuous representations versus "fragmented" discrete ones. Sparse Autoencoders (SAEs) offer a promising bridge between these two paradigms. By learning sparse, interpretable features from the dense activations within neural networks, SAEs can help translate continuous data into more structured, symbolic-like components. This approach aims to combine the robust pattern recognition of neural systems with the logical reasoning capabilities of symbolic AI, advancing the quest for more understandable and capable models. #SparseAutoencoders #AIInterpretability #NeuralNetworks #SymbolicAI #NeuroSymbolic

40 138

Amazing NumPy Cheat Sheet Snippet with 100 exercises for practicing the concept to get hands on to clear the coding round in the interviews #NumPy #codingexams https://t.me/DataScienceM

40 138

I want to share a tool that I genuinely believe can make a real difference for anyone building apps: PacketSDK. Many developers have strong active-user bases but still struggle to increase revenue. That’s exactly why this solution stands out—it adds extra income without disrupting users or interfering with your existing monetization methods. Why I strongly recommend it: * It turns your active users into immediate profit without showing ads. * Integration is fast and straightforward—around 30 minutes. * It works on all platforms: mobile, desktop, TV, Unity, and more.

40 138

📌 I Cleaned a Messy CSV File Using Pandas . Here’s the Exact Process I Follow Every Time. 🗂 Category: DATA SCIENCE 🕒 Date: 2025-11-26 | ⏱️ Read time: 17 min read Stop guessing when cleaning messy CSV files. This article details a repeatable 5-step workflow using Python's Pandas library to systematically diagnose and fix data quality issues. Learn a structured, practical process to transform your data preparation, moving from haphazard fixes to a reliable methodology for any data professional. #Python #Pandas #DataCleaning #DataScience

40 138

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40 138

📌 How I Use AI to Convince Companies to Adopt Sustainability 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-11-26 | ⏱️ Read time: 12 min read Discover how AI, specifically Claude, is being used to champion corporate sustainability. By functioning as a dedicated Supply Chain Sustainability Analyst, the AI can effectively analyze data and guide companies towards adopting greener practices. This article explores a novel and practical use case for large language models in promoting environmental responsibility within complex business supply chains, showcasing the intersection of advanced technology and corporate stewardship. #AI #Sustainability #SupplyChain #ClaudeAI #TechForGood

40 138

📌 RISAT’s Silent Promise: Decoding Disasters with Synthetic Aperture Radar 🗂 Category: DATA SCIENCE 🕒 Date: 2025-11-26 | ⏱️ Read time: 8 min read RISAT satellites are transforming disaster management with Synthetic Aperture Radar (SAR). This advanced technology uses high-resolution physics to interpret microwave echoes, turning complex radar data into real-time flood intelligence. By providing critical, actionable insights from space, SAR enables rapid and effective response to environmental crises, showcasing the power of remote sensing in decoding catastrophic events. #SAR #RemoteSensing #DisasterTech #RISAT

40 138

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40 138

📌 How to Create Professional Articles with LaTeX in Cursor 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-11-25 | ⏱️ Read time: 9 min read Streamline your academic and technical writing by creating professional articles and presentations with LaTeX directly in Cursor. This guide demonstrates how to leverage the editor to rapidly produce high-quality, typeset documents, enhancing your productivity and workflow for polished, professional results. #LaTeX #Cursor #TechnicalWriting #Productivity

40 138

📌 Ten Lessons of Building LLM Applications for Engineers 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-11-25 | ⏱️ Read time: 22 min read Drawing from two years of hands-on experience, this article outlines ten essential lessons for engineers building applications with Large Language Models. Gain practical insights and field-tested advice on structuring projects, optimizing workflows, and implementing effective evaluation strategies to successfully navigate the complexities of LLM development. This guide is for engineers looking to move from theory to production-ready applications. #LLM #AIdevelopment #SoftwareEngineering #MLOps