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

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Сеть:Machine Learning with Python Сирия230 Технологии и приложения3 371...

📈 Аналитический обзор Telegram-канала Machine Learning

Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 140 подписчиков, занимая 3 371 место в категории Технологии и приложения и 230 место в регионе Сирия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 140 подписчиков.

Согласно последним данным от 26 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 429, а за последние 24 часа — 20, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.83%. В первые 24 часа после публикации контент обычно набирает 1.60% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 735 просмотров. В течение первых суток публикация набирает 643 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 2.
Тематические интересы: Контент сосредоточен на ключевых темах, таких как distance, insidead, gpu, learning, degree.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Благодаря высокой частоте обновлений (последние данные получены 27 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.

40 140

Подписчики

+2024 часа

+1017 дней

+42930 день

735

Просмотры поста

~ 64324 часа

~ 87748 часов

1.83%

Коэффициент вовлеченности

~ 3

Постов в день

Ads index

beta

Архив постов

40 141

📌 How Deep Feature Embeddings and Euclidean Similarity Power Automatic Plant Leaf Recognition 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-11-18 | ⏱️ Read time: 14 min read Automatic plant leaf recognition leverages deep feature embeddings to transform leaf images into dense numerical vectors in a high-dimensional space. By calculating the Euclidean similarity between these vector representations, machine learning models can accurately identify and classify plant species. This computer vision technique provides a powerful and scalable solution for botanical and agricultural applications, moving beyond traditional manual identification methods. #ComputerVision #MachineLearning #DeepLearning #FeatureEmbeddings #ImageRecognition

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📌 Why LLMs Aren’t a One-Size-Fits-All Solution for Enterprises 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-11-18 | ⏱️ Read time: 10 min read While Large Language Models (LLMs) excel at extracting value from unstructured enterprise data, they are not a one-size-fits-all solution. Adopting this technology requires a nuanced strategy that considers specific business needs, data privacy, and model customization. For enterprises, understanding the limitations of LLMs is as crucial as recognizing their potential, ensuring a tailored approach is taken to achieve real-world ROI and avoid common implementation pitfalls. #LLM #EnterpriseAI #AIStrategy #GenAI

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📌 How to Build an Over-Engineered Retrieval System 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-11-18 | ⏱️ Read time: 53 min read This article breaks down the process of building a deliberately complex, or 'over-engineered,' retrieval system. It offers a practical look at advanced architectures and methods that, despite their complexity, are used in real-world scenarios for powerful information retrieval and RAG applications. It's an exploration of intricate designs that are surprisingly common in practice. #RAG #SystemDesign #SoftwareArchitecture #InformationRetrieval

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No one believed trading could be this easy—until I found one signal channel that nailed every BTC move! Want to finally see all targets hit, profit after profit? Check this out now before it’s gone. Your next win is waiting! #ad InsideAds

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📌 Introducing ShaTS: A Shapley-Based Method for Time-Series Models 🗂 Category: DATA SCIENCE 🕒 Date: 2025-11-17 | ⏱️ Read time: 9 min read Explaining time-series models with standard tabular Shapley methods can be misleading as they ignore crucial temporal dependencies. A new method, ShaTS (Shapley-based Time-Series), is introduced to solve this problem. Specifically designed for sequential data, ShaTS provides more accurate and reliable interpretations for time-series model predictions, addressing a critical gap in explainable AI for this data type. #ExplainableAI #TimeSeries #ShapleyValues #MachineLearning

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📌 Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 2 🗂 Category: PROGRAMMING 🕒 Date: 2025-11-17 | ⏱️ Read time: 16 min read Feeling JavaScript fatigue? This follow-up tutorial demonstrates how to build a complete ChatGPT-like application using the simplicity of HTMX. Part 2 dives deeper into creating rich, server-rendered interactivity for your web projects, offering a powerful alternative to complex JavaScript frameworks. Learn to leverage HTML attributes for dynamic user experiences without writing extensive client-side code. #HTMX #WebDev #JavaScript #ChatGPT

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📌 Understanding Convolutional Neural Networks (CNNs) Through Excel 🗂 Category: DEEP LEARNING 🕒 Date: 2025-11-17 | ⏱️ Read time: 12 min read Demystify the 'black box' of deep learning by exploring Convolutional Neural Networks (CNNs) with a surprising tool: Microsoft Excel. This hands-on approach breaks down the fundamental operations of CNNs, such as convolution and pooling layers, into understandable spreadsheet calculations. By visualizing the mechanics step-by-step, this method offers a uniquely intuitive and accessible way to grasp how these powerful neural networks learn and process information, making complex AI concepts tangible for developers and data scientists at any level. #DeepLearning #CNN #MachineLearning #Excel #AI

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📌 Javascript Fatigue: HTMX is all you need to build ChatGPT — Part 1 🗂 Category: PROGRAMMING 🕒 Date: 2025-11-17 | ⏱️ Read time: 12 min read Tired of complex JavaScript frameworks? This article demonstrates how to build a dynamic, ChatGPT-style chatbot using a simpler stack. Learn how to leverage the power of HTMX, Python, and standard HTML to create a modern web application while minimizing your reliance on JavaScript. This first part of a series sets the foundation for building interactive UIs with a backend-centric approach, directly addressing the common issue of JavaScript fatigue. #HTMX #Python #WebDevelopment #JavaScriptFatigue

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📌 The Absolute Beginner’s Guide to Pandas DataFrames 🗂 Category: DATA SCIENCE 🕒 Date: 2025-11-17 | ⏱️ Read time: 5 min read New to the Pandas library? This beginner's guide covers the fundamental skill of creating DataFrames. Learn the essential techniques to initialize a DataFrame from common Python data structures, including dictionaries, lists, and NumPy arrays. Mastering this core concept is the perfect first step for anyone starting their data analysis journey in Python. #Python #Pandas #DataAnalysis #DataFrames

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Repost from Free Online Courses

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Repost from Machine Learning with Python

🤖🧠 The Transformer Architecture: How Attention Revolutionized Deep Learning 🗓️ 11 Nov 2025 📚 AI News & Trends The field of artificial intelligence has witnessed a remarkable evolution and at the heart of this transformation lies the Transformer architecture. Introduced by Vaswani et al. in 2017, the paper “Attention Is All You Need” redefined the foundations of natural language processing (NLP) and sequence modeling. Unlike its predecessors – recurrent and convolutional neural networks, ... #TransformerArchitecture #AttentionMechanism #DeepLearning #NaturalLanguageProcessing #NLP #AIResearch

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📌 Stop Worrying about AGI: The Immediate Danger is Reduced General Intelligence (RGI) 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-11-16 | ⏱️ Read time: 7 min read While the tech world debates the distant threat of AGI, a more immediate danger looms: Reduced General Intelligence (RGI). This concept warns of the potential for human cognitive skills to atrophy from over-reliance on AI systems. The article argues that the solution is not to avoid AI, but to use it consciously and deliberately, ensuring it augments our intelligence rather than replaces it. This approach fosters a healthier human-AI collaboration and mitigates the risk of cognitive decline in the age of automation. #RGI #AGI #AIethics #CognitiveSkills

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🤖🧠 Context Engineering 2.0: Redefining Human–Machine Understanding 🗓️ 16 Nov 2025 📚 AI News & Trends As artificial intelligence advances, machines are becoming increasingly capable of understanding and responding to human language. Yet, one crucial challenge remains how can machines truly understand the context behind human intentions? This question forms the foundation of context engineering, a discipline that focuses on designing, organizing and managing contextual information so that AI systems can ... #ContextEngineering #AIEducation #HumanMachineUnderstanding #AIContext #NaturalLanguageProcessing #AIModels

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🤖🧠 OpenAI Evals: The Framework Transforming LLM Evaluation and Benchmarking 🗓️ 16 Nov 2025 📚 AI News & Trends As large language models (LLMs) continue to reshape industries from education and healthcare to marketing and software development – the need for reliable evaluation methods has never been greater. With new models constantly emerging, developers and researchers require a standardized system to test, compare and understand model performance across real-world scenarios. This is where OpenAI ... #OpenAIEvals #LLMEvaluation #Benchmarking #LargeLanguageModels #AIResearch #ModelEvaluation

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📌 I Built an IOS App in 3 Days with Literally No Prior Swift Knowledge 🗂 Category: AI APPLICATIONS 🕒 Date: 2025-11-16 | ⏱️ Read time: 6 min read A developer shares their experience of building a functional iOS app in only three days without any prior Swift knowledge. This journey highlights the power of leveraging AI tools and a "vibe coding" approach to overcome steep learning curves and accelerate the development process. The article offers practical insights for aspiring solopreneurs and developers looking to rapidly prototype and launch new projects, demonstrating how modern technology can democratize app creation. #iOSDev #AI #AppDevelopment #Solopreneur

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🤖🧠 Skyvern: The Future of Browser Automation Powered by AI and Computer Vision 🗓️ 16 Nov 2025 📚 AI News & Trends In today’s fast-evolving digital landscape, automation plays a crucial role in enhancing productivity, efficiency and innovation. Yet, traditional browser automation tools often struggle with complexity, maintenance and reliability. They rely heavily on DOM parsing, XPaths and rigid scripts that easily break when websites change their layout. Enter Skyvern, an open-source, AI-driven browser automation platform developed ... #Skyvern #BrowserAutomation #AIDriven #ComputerVision #OpenSource #WebAutomation

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🤖🧠 Steel Browser: The Open-Source Browser API Powering AI Agents and Automation 🗓️ 16 Nov 2025 📚 AI News & Trends The evolution of artificial intelligence has ushered in a new era of automation where AI agents can perform complex digital tasks with minimal human intervention. However, one of the biggest challenges for developers building these systems is browser automation managing sessions, proxies, cookies and debugging environments. This is where Steel Browser comes into play. Steel ... #SteelBrowser #OpenSource #BrowserAutomation #AIAgents #WebScraping #DigitalAutomation

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📌 I Measured Neural Network Training Every 5 Steps for 10,000 Iterations 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-11-15 | ⏱️ Read time: 9 min read A deep dive into the mechanics of neural network training. This detailed analysis meticulously measures key training metrics every 5 steps over 10,000 iterations, providing a high-resolution view of the learning process. The findings offer granular insights into model convergence and the subtle dynamics often missed by standard monitoring, making it a valuable read for ML practitioners and researchers seeking to better understand how models learn. #NeuralNetworks #MachineLearning #DeepLearning #DataAnalysis #ModelTraining

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📌 How to Automate Workflows with AI 🗂 Category: AGENTIC AI 🕒 Date: 2025-11-15 | ⏱️ Read time: 7 min read Unlock the power of AI to streamline your operations. This guide details how to transform tedious manual processes into intelligent, automated workflows. Learn to identify key opportunities, select the right tools, and implement effective solutions to boost efficiency, reduce errors, and drive business innovation. #AI #WorkflowAutomation #ProcessOptimization