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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Red:📈 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
Archivo de publicaciones
40 323
📌 5 Essential Tips Learned from My Data Science Journey
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-02 | ⏱️ Read time: 7 min read
Personal reflections on my 10-year data odyssey
40 323
📌 Awesome Plotly with code series (Part 9): To dot, to slope or to stack?
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-02 | ⏱️ Read time: 14 min read
Simple methods to replace cluttered bar charts with crisp, reader-friendly visuals.
40 323
📌 Supercharge Your RAG with Multi-Agent Self-RAG
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-02-05 | ⏱️ Read time: 15 min read
Introduction Many of us might have tried to build a RAG application and noticed it…
40 323
📌 Training Large Language Models: From TRPO to GRPO
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-02-05 | ⏱️ Read time: 10 min read
DeepSeek has recently made quite a buzz in the AI community, thanks to its impressive…
40 323
📌 Myths vs. Data: Does an Apple a Day Keep the Doctor Away?
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-05 | ⏱️ Read time: 10 min read
Introduction “Money can’t buy happiness.” “You can’t judge a book by its cover.” “An apple…
40 323
📌 A Visual Guide to How Diffusion Models Work
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-06 | ⏱️ Read time: 26 min read
This article is aimed at those who want to understand exactly how diffusion models work,…
40 323
📌 Deep Dive into WebSockets and Their Role in Client-Server Communication
🗂 Category:
🕒 Date: 2025-02-03 | ⏱️ Read time: 9 min read
How WebSockets work, its tradeoffs, and how to design a real time messaging app
40 323
📌 How to Find Seasonality Patterns in Time Series
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-03 | ⏱️ Read time: 7 min read
Using Fourier Transform to detect seasonal components
40 323
📌 How to Get Promoted as a Data Scientist
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-03 | ⏱️ Read time: 7 min read
Advice from a Lead Data Scientist with 2 promotions in under 2 years
40 323
📌 Neural Networks – Intuitively and Exhaustively Explained
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-03 | ⏱️ Read time: 28 min read
An in-depth exploration of the most fundamental architecture in modern AI.
40 323
📌 Show and Tell
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-02-03 | ⏱️ Read time: 18 min read
Implementing one of the earliest neural image caption generator models with PyTorch.
40 323
📌 Towards Data Science is Launching as an Independent Publication
🗂 Category:
🕒 Date: 2025-02-03 | ⏱️ Read time: 7 min read
Since founding Towards Data Science in 2016, we’ve built the largest publication on Medium with…
40 323
📌 ML Feature Management: A Practical Evolution Guide
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-04 | ⏱️ Read time: 5 min read
In the world of machine learning, we obsess over model architectures, training pipelines, and hyper-parameter…
40 323
“No one ever told me the secret to waking up UNSTOPPABLE—until I found this…”
Want to know the 2 habits that turned average minds into legends? Don’t make the mistake I did—miss out.
Here’s what changed everything
#إعلان InsideAds
40 323
📌 From Resume to Cover Letter Using AI and LLM, with Python and Streamlit
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-02-05 | ⏱️ Read time: 16 min read
DISCLAIMER: The idea of doing Cover Letter or even Resume with AI does not obviously…
40 323
📌 Supercharge Your RAG with Multi-Agent Self-RAG
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-02-05 | ⏱️ Read time: 15 min read
Introduction Many of us might have tried to build a RAG application and noticed it…
40 323
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40 323
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40 323
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40 323
Why does a glass of Chardonnay taste so creamy, while another feels crisp and fresh? Unlock the secrets behind wine’s flavors and explore hidden gems, honest reviews, and fascinating wine stories—without snobbery.
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