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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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📈 Análisis del canal de Telegram Machine Learning

El canal Machine Learning (@machinelearning9) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 244 suscriptores, ocupando la posición 3 343 en la categoría Tecnologías y Aplicaciones y el puesto 227 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 244 suscriptores.

Según los últimos datos del 05 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 346, y en las últimas 24 horas de 22, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.97%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.86% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 794 visualizaciones. En el primer día suele acumular 749 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
  • Intereses temáticos: El contenido se centra en temas clave como distance, insidead, gpu, learning, degree.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 06 julio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

40 244
Suscriptores
+2224 horas
+987 días
+34630 días
Archivo de publicaciones
📌 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