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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Análisis del canal de Telegram Machine Learning with Python

El canal Machine Learning with Python (@codeprogrammer) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 68 579 suscriptores, ocupando la posición 2 404 en la categoría Educación y el puesto 4 688 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 579 suscriptores.

Según los últimos datos del 25 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 227, y en las últimas 24 horas de -9, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.45%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.52% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 2 369 visualizaciones. En el primer día suele acumular 1 042 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 6.
  • Intereses temáticos: El contenido se centra en temas clave como insidead, learning, degree, evaluation, algorithm.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 octubre, 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 Educación.

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68 579
Suscriptores
-924 horas
-237 días
+22730 días
Archivo de publicaciones
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Repost from Machine Learning
I found a great resource for interactive learning about machine learning and AI – VizLearn. You can experiment with gradient descent, SVM, PCA, the Bayesian method, BPE tokenization, Q/K/V, KV-cache, quantization, and much more. You can change the input data and see how the calculations themselves change. It's free and doesn't require registration. https://vizlearn.in https://t.me/MachineLearning9

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A collection of explanations for key concepts and scientific papers in machine learning: https://github.com/dair-ai/ML-Papers-Explained

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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Repost from Machine Learning
Uniface Automate face detection, recognition, and analysis of key facial landmarks with the Uniface Python library. https://g
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Repost from Machine Learning
OpenAI researcher Alice Liu went through 57 interviews before being hired, and then openly shared her entire preparation and
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