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 68 482 suscriptores, ocupando la posición 2 406 en la categoría Educación y el puesto 4 586 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 482 suscriptores.
Según los últimos datos del 04 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -75, y en las últimas 24 horas de 7, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.38%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.57% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 314 visualizaciones. En el primer día suele acumular 1 073 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 9.
- 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 05 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.
68 482
Suscriptores
+724 horas
-597 días
-7530 días
Archivo de publicaciones
🖥 Get Started with Python
A good course on Python from Google.
More than 30 hours of relevant materials that will help you get into the topic.
Here the basic concepts of programming in Python and other features are discussed. Ideal if you have long wanted to try yourself in IT.
📌 Course
http://t.me/codeprogrammer ⭐️
🔒 #Python #COURSES
🗂 A collection of the best free courses
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💠 data science
1️⃣ Python for Everybody Course : A great course for beginners to learn Python.
2️⃣ Data analysis with Python course : This course introduces you to data analysis techniques with Python.
3️⃣ Databases & SQL course : You will learn how to manage databases with SQL.
4️⃣ Intro to Inferential Statistics course : This course teaches you how to make predictions by learning statistics.
5️⃣ ML Zoomcamp course : a practical and practical course for learning machine learning.
🔺 Data engineering
1️⃣ Data Engineering Course : Learn the basics of data engineering.
2️⃣ Data Engineer Learning Path course : a comprehensive road map to become a data engineer.
3️⃣ Database Engineer course : get a specialized degree in database engineering.
4️⃣ Big Data Specialization Course : Get to know big data technologies and their applications.
5️⃣ The Data Eng Zoomcamp course : a practical course to learn data engineering.
🔺 machine learning
1️⃣ Intro to ML course : an introductory and self-paced course to start machine learning.
2️⃣ ML for Everybody course : A simple approach to learning machine learning concepts.
3️⃣ ML in Python course : focus on machine learning with Python and Scikit-Learn.
4️⃣ ML Crash Course : A quick but comprehensive introduction to machine learning.
5️⃣ CS229 : ML : An advanced course for those who want to deepen their knowledge.
🔻 Machine Learning Operations (MLOps)
1️⃣ Python Essentials for MLOps course : an essential course for MLOps enthusiasts..
2️⃣ MLOps for Beginners Course : A great starting point for MLOps newbies.
3️⃣ ML Engineering Course : A set of courses for deep entry into the world of MLOps.
4️⃣ MLOps Specialization Course : Focus on operational aspects of machine learning.
5️⃣ Made With ML course : a special course that combines machine learning with practical applications.
🔹 Generative artificial intelligence
1️⃣ Generative AI for Beginners course : building generative artificial intelligence apps.
2️⃣ Generative AI Fundamentals course : getting to know the basic principles of generative artificial intelligence.
3️⃣ Intro to Gen AI course : from learning large language models to understanding the principles of responsible artificial intelligence.
4️⃣ Generative AI with LLMs course : Learn business applications of artificial intelligence with AWS experts in a practical way.
5️⃣ Generative AI for Everyone course : This course tells you what generative artificial intelligence is, how it works, and what uses and limitations it has.
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📢 Zuckerberg Releases Free ChatGPT Competitor: Llama 3.1!
Mark Zuckerberg just launched Llama 3.1, a next-gen AI model with the largest dataset ever. Available in 8B, 70B, and 405B versions, it boasts a 128k token context size.
Key Highlights:
• Performance: Outperforms GPT-4o and Claude 3.5 in general knowledge, math, and translation.
• Accessibility: Downloadable by anyone, bringing advanced AI within reach.
• Strategic Move: Meta applies pressure on OpenAI with this open-source release. You probably now understand why OpenAI showed GPT-4o mini a week ago and made it so cheap - soon we will have very smart models that run very fast on any hardware.
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• on Hugging Face: Llama 3.1 on Hugging Face
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