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 68 459 suscriptores, ocupando la posición 2 403 en la categoría Educación y el puesto 4 579 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 459 suscriptores.
Según los últimos datos del 02 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -42, y en las últimas 24 horas de -6, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.87%. 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 2 649 visualizaciones. En el primer día suele acumular 1 038 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 8.
- 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 03 noviembre, 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.
68 459
Suscriptores
-624 horas
-1037 días
-4230 días
Archivo de publicaciones
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🔥 MIT has updated its famous course 6.S191: Introduction to Deep Learning.
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Machine Learning Glossary
Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more.
Link: https://ml-cheatsheet.readthedocs.io/en/latest/index.html
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TensorFlow v2.0 Cheat Sheet
#TensorFlow is an open-source software library for highperformance numerical computation. Its flexible architecture enables to easily deploy computation across a variety of platforms (CPUs, GPUs, and TPUs), as well as mobile and edge devices, desktops, and clusters of servers. TensorFlow comes with strong support for machine learning and deep learning.
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Pen and Paper Exercises in MachineLearning
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