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 Сирия232 Технологии и приложения3 398...

📈 Аналитический обзор Telegram-канала Machine Learning

Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 072 подписчиков, занимая 3 398 место в категории Технологии и приложения и 232 место в регионе Сирия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 072 подписчиков.

Согласно последним данным от 23 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 379, а за последние 24 часа — 30, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.92%. В первые 24 часа после публикации контент обычно набирает 1.16% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 770 просмотров. В течение первых суток публикация набирает 466 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
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 24 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.

40 072

Подписчики

+3024 часа

+337 дней

+37930 день

770

Просмотры поста

~ 46624 часа

~ 62048 часов

1.92%

Коэффициент вовлеченности

~ 3

Постов в день

Ads index

beta

Архив постов

40 087

📌 How to Define the Modeling Scope of an Internal Credit Risk Model 🗂 Category: DATA SCIENCE 🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read Dataset construction for Internal Ratings-Based (IRB) Probability of Default (PD) models #DataScience #AI #Python

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📌 Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-02-25 | ⏱️ Read time: 21 min read Understanding the foundational distortion of digital audio from first principles, with worked examples and visual… #DataScience #AI #Python

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📌 Decisioning at the Edge: Policy Matching at Scale 🗂 Category: DATA SCIENCE 🕒 Date: 2026-02-24 | ⏱️ Read time: 13 min read Policy-to-Agency Optimization with PuLP #DataScience #AI #Python

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📌 Optimizing Token Generation in PyTorch Decoder Models 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-24 | ⏱️ Read time: 17 min read Hiding host-device synchronization via CUDA stream interleaving #DataScience #AI #Python

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📌 AI Bots Formed a Cartel. No One Told Them To. 🗂 Category: AGENTIC AI 🕒 Date: 2026-02-24 | ⏱️ Read time: 11 min read Inside the research that shows algorithmic price-fixing isn’t a bug in the code. It’s a… #DataScience #AI #Python

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📌 Optimizing Deep Learning Models with SAM 🗂 Category: DEEP LEARNING 🕒 Date: 2026-02-24 | ⏱️ Read time: 16 min read A deep dive into the Sharpness-Aware-Minimization (SAM) algorithm and how it improves the generalizability of… #DataScience #AI #Python

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📌 Build Effective Internal Tooling with Claude Code 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-02-23 | ⏱️ Read time: 10 min read Use Claude Code to quickly build completely personalized applications #DataScience #AI #Python

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📌 AI in Multiple GPUs: Gradient Accumulation & Data Parallelism 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-23 | ⏱️ Read time: 9 min read Learn and implement gradient accum and data parallelism from scratch in PyTorch #DataScience #AI #Python

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Repost from Machine Learning with Python

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40 087

📌 PySpark for Pandas Users 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-02-23 | ⏱️ Read time: 16 min read Common Pandas operations and their equivalents in PySpark #DataScience #AI #Python

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📌 Is the AI and Data Job Market Dead? 🗂 Category: DATA SCIENCE 🕒 Date: 2026-02-23 | ⏱️ Read time: 8 min read What you should be doing in the current job market #DataScience #AI #Python

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📌 The Reality of Vibe Coding: AI Agents and the Security Debt Crisis 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-02-22 | ⏱️ Read time: 6 min read Why optimizing for speed over safety is leaving applications vulnerable, and how to fix it. #DataScience #AI #Python

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Repost from Machine Learning with Python

🏷 Comprehensive Data Science Roadmap Notes ✅ This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market. 🕡 From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project. 🕑 How to extract real analysis reports and strategies from raw data using statistics and visualization tools. 🕗 You will learn everything from machine learning and advanced algorithms to precise model evaluation. 🕙 Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world. 🕧 How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for. 🌐 #DataScience #DataScience #pytorch #python #Roadmap https://t.me/CodeProgrammer

40 087

Repost from Machine Learning with Python

🏷 Comprehensive Data Science Roadmap Notes ✅ This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market. 🕡 From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project. 🕑 How to extract real analysis reports and strategies from raw data using statistics and visualization tools. 🕗 You will learn everything from machine learning and advanced algorithms to precise model evaluation. 🕙 Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world. 🕧 How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for. ⚡️ Download it Free 👇: https://lve.to/gs6khab8jq 🌐 #DataScience #DataScience #pytorch #python #Roadmap

40 087

Repost from Machine Learning with Python

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📌 Architecting GPUaaS for Enterprise AI On-Prem 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-21 | ⏱️ Read time: 16 min read Multi-tenancy, scheduling, and cost modeling on Kubernetes #DataScience #AI #Python

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📌 From Monolith to Contract-Driven Data Mesh 🗂 Category: DATA SCIENCE 🕒 Date: 2026-02-20 | ⏱️ Read time: 12 min read A pragmatic journey using website analytics as a real-world example #DataScience #AI #Python

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📌 An End-to-End Guide to Beautifying Your Open-Source Repo with Agentic AI 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-02-20 | ⏱️ Read time: 17 min read The guide to automated improvement of scientific and industrial repositories using open-source AI agents #DataScience #AI #Python