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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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Machine Learning with PythonRed:Machine Learning with PythonSiria225Tecnologías y Aplicaciones3 329

📈 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 40 346 suscriptores, ocupando la posición 3 329 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 40 346 suscriptores.

Según los últimos datos del 11 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 393, y en las últimas 24 horas de 17, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.29%. 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 924 visualizaciones. En el primer día suele acumular 702 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 12 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.

40 346
Suscriptores
+1724 horas
+1237 días
+39330 días
Archivo de publicaciones
Machine Learning
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40 351
📌 Why You Should Not Replace Blanks with 0 in Power BI 🗂 Category: DATA ANALYSIS 🕒 Date: 2025-06-20 | ⏱️ Read time: 7 min
📌 Why You Should Not Replace Blanks with 0 in Power BI 🗂 Category: DATA ANALYSIS 🕒 Date: 2025-06-20 | ⏱️ Read time: 7 min read Did someone ask you to replace blank values with 0 in your reports? Maybe you…

Machine Learning
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40 351
📌 Building AI-Powered Low-Code Workflows with n8n 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-23 | ⏱️ Read time: 2
📌 Building AI-Powered Low-Code Workflows with n8n 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-23 | ⏱️ Read time: 27 min read Three powerful workflows that you can apply to your personal life or business today

Machine Learning
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40 351
📌 Building A Modern Dashboard with Python and Taipy 🗂 Category: PROGRAMMING 🕒 Date: 2025-06-23 | ⏱️ Read time: 11 min read
📌 Building A Modern Dashboard with Python and Taipy 🗂 Category: PROGRAMMING 🕒 Date: 2025-06-23 | ⏱️ Read time: 11 min read A guide to building a front-end data application.

Machine Learning
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40 351
📌 Programming, Not Prompting: A Hands-On Guide to DSPy 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-23 | ⏱️ Read ti
📌 Programming, Not Prompting: A Hands-On Guide to DSPy 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-23 | ⏱️ Read time: 16 min read A practical deep dive into declarative AI programming

Machine Learning
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40 351
📌 Reinforcement Learning from Human Feedback, Explained Simply 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-23 | ⏱️ R
📌 Reinforcement Learning from Human Feedback, Explained Simply 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-23 | ⏱️ Read time: 7 min read The one technique that made ChatGPT so smart

Machine Learning
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40 351
📌 Build Multi-Agent Apps with OpenAI’s Agent SDK 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-24 | ⏱️ Read time: 21
📌 Build Multi-Agent Apps with OpenAI’s Agent SDK 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-24 | ⏱️ Read time: 21 min read Creating multi-agent apps is simple with this open-source SDK, and it can be used with…

Machine Learning
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40 351
📌 Why Your Next LLM Might Not Have A Tokenizer 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-24 | ⏱️ Read time: 16 min
📌 Why Your Next LLM Might Not Have A Tokenizer 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-24 | ⏱️ Read time: 16 min read The Tokenizer Has Been a Necessary Evil, but This Radical Approach Shows That It Might…

Machine Learning
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40 351
📌 Agentic AI: Implementing Long-Term Memory 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-24 | ⏱️ Read time: 11 min
📌 Agentic AI: Implementing Long-Term Memory 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-24 | ⏱️ Read time: 11 min read The problem and current solutions

Machine Learning
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40 351
📌 Data Has No Moat! 🗂 Category: DATA SCIENCE 🕒 Date: 2025-06-24 | ⏱️ Read time: 7 min read Only if you ignore data quality
📌 Data Has No Moat! 🗂 Category: DATA SCIENCE 🕒 Date: 2025-06-24 | ⏱️ Read time: 7 min read Only if you ignore data quality

Machine Learning
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40 351
📌 Stop Chasing “Efficiency AI.” The Real Value Is in “Opportunity AI.” 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06
📌 Stop Chasing “Efficiency AI.” The Real Value Is in “Opportunity AI.” 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-25 | ⏱️ Read time: 11 min read Companies pursuing incremental productivity gains risk being displaced by AI-native competitors building entirely new business…

Machine Learning
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40 351
📌 How to Train a Chatbot Using RAG and Custom Data 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-25 | ⏱️ Read time: 6
📌 How to Train a Chatbot Using RAG and Custom Data 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-25 | ⏱️ Read time: 6 min read Retrieval-Augmented Generation made easy with Llama

Machine Learning
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40 351
📌 Economic Cycle Synchronization with Dynamic Time Warping 🗂 Category: ECONOMICS 🕒 Date: 2025-06-25 | ⏱️ Read time: 7 min
📌 Economic Cycle Synchronization with Dynamic Time Warping 🗂 Category: ECONOMICS 🕒 Date: 2025-06-25 | ⏱️ Read time: 7 min read The case of the Eurozone

Machine Learning
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40 351
📌 Use OpenAI Whisper for Automated Transcriptions 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-25 | ⏱️ Read time: 8 m
📌 Use OpenAI Whisper for Automated Transcriptions 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-25 | ⏱️ Read time: 8 min read Streamline your computer interactions using OpenAI’s Whisper model

Machine Learning
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40 351
📌 AI Agent with Multi-Session Memory 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-26 | ⏱️ Read time: 9 min read Bui
📌 AI Agent with Multi-Session Memory 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-26 | ⏱️ Read time: 9 min read Build from scratch using only Python & Ollama (no GPU, no APIKEY)

Machine Learning
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40 351
📌 The Mythical Pivot Point from Buy to Build for Data Platforms 🗂 Category: DATA ENGINEERING 🕒 Date: 2025-06-26 | ⏱️ Read
📌 The Mythical Pivot Point from Buy to Build for Data Platforms 🗂 Category: DATA ENGINEERING 🕒 Date: 2025-06-26 | ⏱️ Read time: 10 min read For companies with data-intensive architectures, there often comes a pivotal point where building in-house data…

Machine Learning
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40 351
📌 Data Science: From School to Work, Part V 🗂 Category: PROGRAMMING 🕒 Date: 2025-06-26 | ⏱️ Read time: 18 min read How to
📌 Data Science: From School to Work, Part V 🗂 Category: PROGRAMMING 🕒 Date: 2025-06-26 | ⏱️ Read time: 18 min read How to profile your Python project

Machine Learning
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40 351
📌 Hitchhiker’s Guide to RAG with ChatGPT API and LangChain 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-26 | ⏱️ Rea
📌 Hitchhiker’s Guide to RAG with ChatGPT API and LangChain 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-26 | ⏱️ Read time: 7 min read Build a simple Python RAG pipeline using your local files as context

Machine Learning
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40 351
📌 A Caching Strategy for Identifying Bottlenecks on the Data Input Pipeline 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-2
📌 A Caching Strategy for Identifying Bottlenecks on the Data Input Pipeline 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-26 | ⏱️ Read time: 16 min read PyTorch model performance analysis and optimization — Part 8

Machine Learning
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📌 Pipelining AI/ML Training Workloads with CUDA Streams 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-26 | ⏱️ Read time: 12
📌 Pipelining AI/ML Training Workloads with CUDA Streams 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-26 | ⏱️ Read time: 12 min read PyTorch Model Performance Analysis and Optimization — Part 9

Machine Learning
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40 351
📌 A Developer’s Guide to Building Scalable AI: Workflows vs Agents 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-27
📌 A Developer’s Guide to Building Scalable AI: Workflows vs Agents 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-27 | ⏱️ Read time: 38 min read A practical guide to choosing between AI agents and workflows for production systems, covering the…