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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 40 373 suscriptores, ocupando la posición 3 327 en la categoría Tecnologías y Aplicaciones y el puesto 225 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 373 suscriptores.

Según los últimos datos del 12 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 399, y en las últimas 24 horas de 24, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.42%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.74% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 979 visualizaciones. En el primer día suele acumular 703 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 4.
  • 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 13 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.

40 373
Suscriptores
+2424 horas
+1257 días
+39930 días
Archivo de publicaciones
📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6
📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6 min read What’s the state of AI in business these days, and how much does it cost…

📌 Useful Python Libraries You Might Not Have Heard Of: Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time
📌 Useful Python Libraries You Might Not Have Heard Of:  Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time: 12 min read Bring time to a standstill in your Python tests

📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min
📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min read How to stand out in a crowded field

📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min re
📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min read The 7 emerging application patterns you should know

📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Re
📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 30 min read Built over 14 days, all locally run, no API keys, cloud services, or subscription fees.

📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read U
📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read Understanding and implementing MobileNetV1 from scratch with PyTorch

📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min
📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min read How hyperparameter tuning visually changes random forests

📌 Should We Use LLMs As If They Were Swiss Knives? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-04 | ⏱️ Read time:
📌 Should We Use LLMs As If They Were Swiss Knives? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 9 min read A logic game performance comparison between popular LLMs and a custom-made algorithm

📌 Tool Masking: The Layer MCP Forgot 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-05 | ⏱️ Read time: 16 min read Tool masking fo
📌 Tool Masking: The Layer MCP Forgot 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-05 | ⏱️ Read time: 16 min read Tool masking for AI improves AI agents: shape MCP tool surfaces to cut tokens and…

📌 Zero-Inflated Data: A Comparison of Regression Models 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-05 | ⏱️ Read time: 13 min
📌 Zero-Inflated Data: A Comparison of Regression Models 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-05 | ⏱️ Read time: 13 min read How to detect it and which model to choose.

📌 AI Operations Under the Hood: Challenges and Best Practices 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-09-05 | ⏱️ Read ti
📌 AI Operations Under the Hood: Challenges and Best Practices 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-09-05 | ⏱️ Read time: 18 min read Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation,…

📌 Showcasing Your Work on HuggingFace Spaces 🗂 Category: PRODUCTIVITY 🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read Buildi
📌 Showcasing Your Work on HuggingFace Spaces 🗂 Category: PRODUCTIVITY 🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read Building an app is exciting – but sharing it is where the real value kicks…

📌 How to Context Engineer to Optimize Question Answering Pipelines 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-05 |
📌 How to Context Engineer to Optimize Question Answering Pipelines 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read Learn how to apply context engineering to enhance your question answering systems.

📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6
📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6 min read What’s the state of AI in business these days, and how much does it cost…

📌 Useful Python Libraries You Might Not Have Heard Of: Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time
📌 Useful Python Libraries You Might Not Have Heard Of:  Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time: 12 min read Bring time to a standstill in your Python tests

📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min
📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min read How to stand out in a crowded field

📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min re
📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min read The 7 emerging application patterns you should know

📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Re
📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 30 min read Built over 14 days, all locally run, no API keys, cloud services, or subscription fees.

📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read U
📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read Understanding and implementing MobileNetV1 from scratch with PyTorch

📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min
📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min read How hyperparameter tuning visually changes random forests