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 67 816 suscriptores, ocupando la posición 2 417 en la categoría Educación y el puesto 5 033 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 67 816 suscriptores.

Según los últimos datos del 10 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 49, y en las últimas 24 horas de -10, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.61%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.40% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 1 770 visualizaciones. En el primer día suele acumular 1 628 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 7.
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 11 junio, 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.

67 816

Suscriptores

-1024 horas

-17 días

+4930 días

1 770

Visitas de la publicación

~ 1 62824 horas

~ 2 19748 horas

2.61%

Tasa de compromiso

~ 3

Mensajes por día

Ads index

beta

Archivo de publicaciones

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58k, thanks ❤️

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Keras Cheat Sheet: Neural Networks in Python By Sandeep Sharma

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Python #Pandas Cheat Sheet 🐼

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🏳️‍🌈 "NumPy Library" Tutorial 👨🏻‍💻 For the past few days, I've been busy preparing this comprehensive tutorial on the NumPy library for data science, trying to cover all the tips and tricks of this library. ✅ Why is this booklet different? Because it is not written based on just theoretical concepts, but is the result of my own experiences and learning. It has real and practical examples that will help you better understand #NumPy concepts and use them in your projects.💯

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https://t.me/HusseinSheikho/s/63 You too?!!

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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

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