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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
📌 Spoiler Alert: The Magic of RAG Does Not Come from AI 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-17 | ⏱️ Read time: 10
📌 Spoiler Alert: The Magic of RAG Does Not Come from AI 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-17 | ⏱️ Read time: 10 min read Why retrieval, not generation, makes RAG systems magical

📌 How to Reduce Python Runtime for Demanding Tasks 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-17 | ⏱️ Read time: 8 min read
📌 How to Reduce Python Runtime for Demanding Tasks 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-17 | ⏱️ Read time: 8 min read Practical techniques to accelerate heavy workloads with GPU optimization in Python

📌 From Local to Cloud: Estimating GPU Resources for Open-Source LLMs 🗂 Category: 🕒 Date: 2024-11-18 | ⏱️ Read time: 4 min
📌 From Local to Cloud: Estimating GPU Resources for Open-Source LLMs 🗂 Category: 🕒 Date: 2024-11-18 | ⏱️ Read time: 4 min read Estimating GPU memory for deploying the latest open-source LLMs

📌 Data Validation with Pandera in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-18 | ⏱️ Read time: 10 min read Validatin
📌 Data Validation with Pandera in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-18 | ⏱️ Read time: 10 min read Validating your Dataframes for Production ML Pipelines

📌 Creating a frontend for your ML application with Vercel V0 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-18 | ⏱️ Read tim
📌 Creating a frontend for your ML application with Vercel V0 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-18 | ⏱️ Read time: 9 min read Develop an appealing frontend application using v0 by Vercel

📌 Navigating Networks with NetworkX: A Short Guide to Graphs in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-18 | ⏱️ Re
📌 Navigating Networks with NetworkX: A Short Guide to Graphs in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-18 | ⏱️ Read time: 16 min read Explore NetworkX for building, analyzing, and visualizing graphs in Python. Discovering Insights in Connected Data.

📌 Increasing Transformer Model Efficiency Through Attention Layer Optimization 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date:
📌 Increasing Transformer Model Efficiency Through Attention Layer Optimization 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-18 | ⏱️ Read time: 16 min read How paying “better” attention can drive ML cost savings

📌 The Metrics of Continual Learning 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-18 | ⏱️ Read time: 4 min read Thes
📌 The Metrics of Continual Learning 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-18 | ⏱️ Read time: 4 min read These three metrics are commonly used

📌 Building a Local Voice Assistant with LLMs and Neural Networks on Your CPU Laptop 🗂 Category: DATA SCIENCE 🕒 Date: 2024-
📌 Building a Local Voice Assistant with LLMs and Neural Networks on Your CPU Laptop 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-19 | ⏱️ Read time: 6 min read A practical guide to run lightweight LLMs using python

📌 Dance between dense and sparse embeddings: Enabling Hybrid Search in LangChain-Milvus 🗂 Category: 🕒 Date: 2024-11-19 | ⏱
📌 Dance between dense and sparse embeddings: Enabling Hybrid Search in LangChain-Milvus 🗂 Category: 🕒 Date: 2024-11-19 | ⏱️ Read time: 7 min read Dance Between Dense and Sparse Embeddings: Enabling Hybrid Search in LangChain-Milvus How to create and…

📌 Multimodal Models – LLMs that can see and hear 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-19 | ⏱️ Read time: 10 min re
📌 Multimodal Models – LLMs that can see and hear 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-19 | ⏱️ Read time: 10 min read An introduction with example Python code

📌 The Root Cause of Why Organizations Fail With Data & AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-19 | ⏱️ Read
📌 The Root Cause of Why Organizations Fail With Data & AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-19 | ⏱️ Read time: 34 min read A guide to be successful with the strategic groundwork required

📌 NLP Illustrated, Part 1: Text Encoding 🗂 Category: DEEP LEARNING 🕒 Date: 2024-11-19 | ⏱️ Read time: 10 min read An illus
📌 NLP Illustrated, Part 1: Text Encoding 🗂 Category: DEEP LEARNING 🕒 Date: 2024-11-19 | ⏱️ Read time: 10 min read An illustrated guide to text-to-number translation, with code

📌 Linear programming: Integer Linear Programming with Branch and Bound 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-19 | ⏱️ Re
📌 Linear programming: Integer Linear Programming with Branch and Bound 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-19 | ⏱️ Read time: 11 min read Part 4: Extending linear programming optimization to discrete decision variables

📌 Third-Year Work Anniversary as a Data Scientist: Growth, Reflections and Acceptance 🗂 Category: CAREER ADVICE 🕒 Date: 20
📌 Third-Year Work Anniversary as a Data Scientist: Growth, Reflections and Acceptance 🗂 Category: CAREER ADVICE 🕒 Date: 2024-11-19 | ⏱️ Read time: 8 min read A letter to myself and fellow data scientists

📌 How to Answer Business Questions with Data 🗂 Category: BUSINESS 🕒 Date: 2024-11-19 | ⏱️ Read time: 15 min read Data anal
📌 How to Answer Business Questions with Data 🗂 Category: BUSINESS 🕒 Date: 2024-11-19 | ⏱️ Read time: 15 min read Data analysis is the key to drive business decisions through answering abstract business questions but…

📌 Collision Risk in Hash-Based Surrogate Keys 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-11-20 | ⏱️ Read time: 14 min read
📌 Collision Risk in Hash-Based Surrogate Keys 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-11-20 | ⏱️ Read time: 14 min read Various aspects and real-life analogies of the odds of having a hash collision when computing…

📌 Einstein Notation: A New Lens on Transformers 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-20 | ⏱️ Read time: 9 min read
📌 Einstein Notation: A New Lens on Transformers 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-20 | ⏱️ Read time: 9 min read Transforming the Math of the Transformer Model

📌 Water Cooler Small Talk: Why Does the Monty Hall Problem Still Bother Us? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-20 |
📌 Water Cooler Small Talk: Why Does the Monty Hall Problem Still Bother Us? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-20 | ⏱️ Read time: 10 min read A look at the counterintuitive mathematics of game show puzzles

📌 LoRA Fine-Tuning On Your Apple Silicon MacBook 🗂 Category: 🕒 Date: 2024-11-20 | ⏱️ Read time: 11 min read Let’s Go Step-
📌 LoRA Fine-Tuning On Your Apple Silicon MacBook 🗂 Category: 🕒 Date: 2024-11-20 | ⏱️ Read time: 11 min read Let’s Go Step-By-Step Fine-Tuning On Your MacBook