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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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📈 Аналитический обзор Telegram-канала Machine Learning

Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 244 подписчиков, занимая 3 343 место в категории Технологии и приложения и 227 место в регионе Сирия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 244 подписчиков.

Согласно последним данным от 05 июля, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 346, а за последние 24 часа — 22, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.97%. В первые 24 часа после публикации контент обычно набирает 1.86% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 794 просмотров. В течение первых суток публикация набирает 749 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 06 июля, 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.

40 244
Подписчики
+2224 часа
+987 дней
+34630 день
Архив постов
📌 A Story of Long Tails: Why Uncertainty in Marketing Mix Modelling is Important 🗂 Category: MARKETING 🕒 Date: 2024-11-27
📌 A Story of Long Tails: Why Uncertainty in Marketing Mix Modelling is Important 🗂 Category: MARKETING 🕒 Date: 2024-11-27 | ⏱️ Read time: 30 min read "Details matter. It’s worth waiting to get it right." — Steve Jobs What if the…

📌 Saving Pandas DataFrames Efficiently and Quickly – Parquet vs Feather vs ORC vs CSV 🗂 Category: DATA SCIENCE 🕒 Date: 202
📌 Saving Pandas DataFrames Efficiently and Quickly – Parquet vs Feather vs ORC vs CSV 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 15 min read Speed, RAM, size and convenience. Which storage method is best?

📌 Use Tablib to Handle Simple Tabular Data in Python 🗂 Category: 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Sometimes
📌 Use Tablib to Handle Simple Tabular Data in Python 🗂 Category: 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Sometimes a Shallow Abstraction is more Valuable than Performance

📌 Introducing the New Anthropic PDF Processing API 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min r
📌 Introducing the New Anthropic PDF Processing API 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read Anthropic Claude 3.5 now understands PDF input

📌 Roadmap to Becoming a Data Scientist, Part 1: Maths 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min r
📌 Roadmap to Becoming a Data Scientist, Part 1: Maths 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Identifying fundamental math skills to master for aspiring Data Scientists

📌 How to Develop an Effective AI-Powered Legal Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-27 | ⏱️ Read time: 1
📌 How to Develop an Effective AI-Powered Legal Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Create a machine-learning-based search into legal decisions

📌 Level Up Your Coding Skills with Python Threading 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read
📌 Level Up Your Coding Skills with Python Threading 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read Learn how to use queues, daemon threads, and events in a Machine Learning project

📌 Effortless Data Handling: Find Variables Across Multiple Data Files with R 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 |
📌 Effortless Data Handling: Find Variables Across Multiple Data Files with R 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read A practical solution with code and workflow

📌 AI Agents in Networking Industry 🗂 Category: 🕒 Date: 2024-11-27 | ⏱️ Read time: 11 min read AI Agents for deploying, con
📌 AI Agents in Networking Industry 🗂 Category: 🕒 Date: 2024-11-27 | ⏱️ Read time: 11 min read AI Agents for deploying, configuring and monitoring Networks

📌 How to Prune LLaMA 3.2 and Similar Large Language Models 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-11-27 | ⏱️ Read
📌 How to Prune LLaMA 3.2 and Similar Large Language Models 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-11-27 | ⏱️ Read time: 17 min read This article presents a structured pruning technique for state-of-the-art models, that uses a GLU architecture,…

📌 How to Transition from Engineering to Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 7 min rea
📌 How to Transition from Engineering to Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 7 min read AI for engineers: experience of an engineering graduate

📌 How Can Self-Driving Cars Work Better? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-28 | ⏱️ Read time: 8 min read The far-re
📌 How Can Self-Driving Cars Work Better? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-28 | ⏱️ Read time: 8 min read The far-reaching implications of Waymo’s EMMA and other end-to-end driving systems

📌 How to Select the 5 Most Relevant Documents for AI Search 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-19 | ⏱️ Read
📌 How to Select the 5 Most Relevant Documents for AI Search 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-19 | ⏱️ Read time: 10 min read Improve the document retrieval step of your RAG pipeline

📌 An Interactive Guide to 4 Fundamental Computer Vision Tasks Using Transformers 🗂 Category: COMPUTER VISION 🕒 Date: 2025-
📌 An Interactive Guide to 4 Fundamental Computer Vision Tasks Using Transformers 🗂 Category: COMPUTER VISION 🕒 Date: 2025-09-19 | ⏱️ Read time: 14 min read An overview of 4 fundamental computer vision tasks – image classification, image segmentation, image captioning…

📌 LLMs.txt Explained 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-28 | ⏱️ Read time: 6 min read Your guide to the w
📌 LLMs.txt Explained 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-28 | ⏱️ Read time: 6 min read Your guide to the web’s new LLM-ready content standard

Я получил свои первые TON за 5 минут — и ничем не рисковал! «Думал, что это очередной фейк… но TON реально пришли на счет» Хо
Я получил свои первые TON за 5 минут — и ничем не рисковал! «Думал, что это очередной фейк… но TON реально пришли на счет» Хочешь также? Узнай, как получить до 10 TON без вложенийуже сегодня. #ad InsideAds.

📌 The Economics of Artificial Intelligence – what does automation mean for workers? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒
📌 The Economics of Artificial Intelligence – what does automation mean for workers? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-25 | ⏱️ Read time: 40 min read Despite tremendous progress in AI, the economic implications of AI remain inadequately understood, with unsatisfactory…

📌 RAGOps Guide: Building and Scaling Retrieval Augmented Generation Systems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 20
📌 RAGOps Guide: Building and Scaling Retrieval Augmented Generation Systems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-26 | ⏱️ Read time: 28 min read The Architecture, Operational Layers, and Best Practices for Effective RAG Implementation

📌 Every Step of the Machine Learning Life Cycle Simply Explained 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-26 | ⏱️ Read tim
📌 Every Step of the Machine Learning Life Cycle Simply Explained 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-26 | ⏱️ Read time: 18 min read A comprehensive guide to the ML life cycle with examples in Python

“Sadece 8 PUMP ile işlem başlatabileceğini kimse bana inanmamıştı!” Her referans 2 PUMP veriyor, görevleri tamamla ve sırrı b
“Sadece 8 PUMP ile işlem başlatabileceğini kimse bana inanmamıştı!” Her referans 2 PUMP veriyor, görevleri tamamla ve sırrı burada keşfet — kimse fark etmeden airdropları topla! #ad InsideAds