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

Red:Machine Learning with Python Siria225 Tecnologías y Aplicaciones3 332...

📈 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 40 323 suscriptores, ocupando la posición 3 332 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 40 323 suscriptores.

Según los últimos datos del 09 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 378, y en las últimas 24 horas de 30, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.23%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.95% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 897 visualizaciones. En el primer día suele acumular 788 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 10 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.

40 323

Suscriptores

+3024 horas

+1067 días

+37830 días

897

Visitas de la publicación

~ 78824 horas

~ 1 02448 horas

2.23%

Tasa de compromiso

~ 2

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 323

📌 A Clear Intro to MCP (Model Context Protocol) with Code Examples 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-25 | ⏱️ Read time: 16 min read MCP is a way to democratize access to tools for AI Agents. In this article…

40 323

📌 Testing the Power of Multimodal AI Systems in Reading and Interpreting Photographs, Maps, Charts and More 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-03-25 | ⏱️ Read time: 30 min read Can multimodal AI systems consisting in LLMs with vision capabilities understand figures and extract information…

40 323

📌 Data-Driven March Madness Predictions 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-25 | ⏱️ Read time: 11 min read How to optimize your bracket systematically, no college basketball knowledge required

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📌 Attractors in Neural Network Circuits: Beauty and Chaos 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-03-25 | ⏱️ Read time: 12 min read Neural networks under a different lens: generating basins of attraction in a shift register NN

40 323

📌 The Ultimate AI/ML Roadmap For Beginners 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-25 | ⏱️ Read time: 10 min read How to learn AI/ML from scratch

40 323

📌 Uncertainty Quantification in Machine Learning with an Easy Python Interface 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-03-26 | ⏱️ Read time: 15 min read The ML Uncertainty Package

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📌 AI Agents from Scratch: Iterations & Chains 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-26 | ⏱️ Read time: 7 min read From Zero to Hero using only Python & Ollama (no GPU, no APIKEY)

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📌 Automate Supply Chain Analytics Workflows with AI Agents using n8n 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-26 | ⏱️ Read time: 6 min read What if you could automate complete supply chain analytics workflows with low-code solutions?

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📌 About Towards Data Science 🗂 Category: ABOUT 🕒 Date: 2025-03-27 | ⏱️ Read time: 2 min read We strive to present well-written, informative articles that our audience is excited to read.

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📌 How to Streamline Your Work with Agents and LLMs 🗂 Category: THE VARIABLE 🕒 Date: 2025-03-27 | ⏱️ Read time: 3 min read This week, we focus on helping you improve your workflow with AI.

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📌 Talk to Videos 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-03-27 | ⏱️ Read time: 28 min read Developing an interactive AI application for video-based learning in education and business

40 323

📌 Japanese-Chinese Translation with GenAI: What Works and What Doesn’t 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-27 | ⏱️ Read time: 20 min read Evaluating GenAI in Japanese-Chinese translation: current limits and opportunities

40 323

📌 Data Science: From School to Work, Part III 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-27 | ⏱️ Read time: 12 min read Good practices for Python error handling and logging

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40 323

📌 From Physics to Probability: Hamiltonian Mechanics for Generative Modeling and MCMC 🗂 Category: MATH 🕒 Date: 2025-03-28 | ⏱️ Read time: 17 min read Hamiltonian mechanics is a way to describe how physical systems, like planets or pendulums, move…

40 323

📌 AI Agents from Scratch: Multi-Agent System 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-28 | ⏱️ Read time: 14 min read From Zero to Hero using only Python & Ollama (no GPU, no APIKEY)

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📌 Master the 3D Reconstruction Process: A Step-by-Step Guide 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-28 | ⏱️ Read time: 17 min read Learn the complete 3D reconstruction pipeline from feature extraction to dense matching. Master photogrammetry with…

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📌 A Little More Conversation, A Little Less Action — A Case Against Premature Data Integration 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-28 | ⏱️ Read time: 14 min read Running a large data integration project before embarking on the ML part is easily a…

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📌 The Art of Hybrid Architectures 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-28 | ⏱️ Read time: 32 min read Combining CNNs and Transformers to Elevate Fine-Grained Visual Classification

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📌 Understanding the Tech Stack Behind Generative AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-31 | ⏱️ Read time: 22 min read From foundation models to vector databases and AI agents — what makes modern AI work