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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 68 471 suscriptores, ocupando la posición 2 400 en la categoría Educación y el puesto 4 598 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 471 suscriptores.

Según los últimos datos del 31 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 12, y en las últimas 24 horas de -24, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.99%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.46% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 2 735 visualizaciones. En el primer día suele acumular 998 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 01 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.

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68 471
Suscriptores
-2424 horas
-947 días
+1230 días
Archivo de publicaciones
Repost from Machine Learning
📌 How to Build Effective Agentic Systems with LangGraph 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-30 | ⏱️ Read time: 12 min r
📌 How to Build Effective Agentic Systems with LangGraph 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-30 | ⏱️ Read time: 12 min read Create AI workflows with agentic frameworks

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

Please help me collect a donation for an urgent and very necessary matter. The amount is $300 I hope everyone will help me PayPal: https://www.paypal.me/HusseinSheikho Usdt TRC-20 Address: TMzAr8AFcZ1n5RXZa3BHPXHBRqugx9Skr7

“Nobody believed me when I said I made +200 pips in ONE day. But look at this—members are collecting profits while others are
“Nobody believed me when I said I made +200 pips in ONE day. But look at this—members are collecting profits while others are still doubting. Do you want to see how it’s really done? Check here before you miss the next payout! #ad InsideAds.

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No one ever told me you could earn +200 pips in a single day—yet here I am, watching my balance grow. Want to see how I did i
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“Nobody believed me when I said I made +200 pips in ONE day. But look at this—members are collecting profits while others are
“Nobody believed me when I said I made +200 pips in ONE day. But look at this—members are collecting profits while others are still doubting. Do you want to see how it’s really done? Check here before you miss the next payout! #ad InsideAds.

Repost from Machine Learning
📌 PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks 🗂 Category: DEEP LEARNING 🕒 Date: 2
📌 PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-24 | ⏱️ Read time: 15 min read Deep learning is shaping our world as we speak. In fact, it has been slowly…

Most of the time, you regret helping others in general, because not everyone appreciates your hard work or the effort it takes you to spread a piece of information, even if it's quoted

Join today and get 150% bonus! We will turn £100->£250 #ad InsideAds
Join today and get 150% bonus! We will turn £100->£250 #ad InsideAds

Repost from Machine Learning
📌 Paper Walkthrough: Attention Is All You Need 🗂 Category: DEEP LEARNING 🕒 Date: 2024-11-03 | ⏱️ Read time: 46 min read Th
📌 Paper Walkthrough: Attention Is All You Need 🗂 Category: DEEP LEARNING 🕒 Date: 2024-11-03 | ⏱️ Read time: 46 min read The complete guide to implementing a Transformer from scratch

Repost from Machine Learning
📌 Building a Convolutional Neural Network (CNNs) from Scratch 🗂 Category: 🕒 Date: 2024-11-05 | ⏱️ Read time: 15 min read L
📌 Building a Convolutional Neural Network (CNNs) from Scratch 🗂 Category: 🕒 Date: 2024-11-05 | ⏱️ Read time: 15 min read Line-by-Line, Let’s Build a ResNet Classifier on the MNIST-Fashion Dataset

Join today and get 150% bonus! We will turn £100->£250 #ad InsideAds
Join today and get 150% bonus! We will turn £100->£250 #ad InsideAds

Jeden Tag verpassen, wie andere Top-Deals abstauben? Warum noch länger zu viel bezahlen? Spare jetzt bis zu 80 % bei Angebote
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💯 Use Kaggle like a pro with this method! 👨🏻‍💻 Never underestimate Kaggle! One of the best ways to start learning data sc
💯 Use Kaggle like a pro with this method! 👨🏻‍💻 Never underestimate Kaggle! One of the best ways to start learning data science and ML is Kaggle. A place where theory turns into practice, beginners become professionals, and skills turn into value. 🎯 This roadmap is the key to practical use of this amazing platform:👇 ⬅️ Step one: Strengthen your basic skills! ✏️ Start with Kaggle's short and free courses. Practical, focused, and suitable for beginners. ✅ Python ⬅️ Link ☑️ Introduction to Machine Learning ⬅️ Link ✔️ Introduction to Deep Learning ⬅️ Link ✔️ Introduction to SQL ⬅️ Link ✔️ Introduction to Game AI and RL ⬅️ Link 📝 Complete list of courses ⬅️Link                    ➖➖➖➖➖➖ ⬅️ Step two: Apply what you’ve learned. ✏️ Learning alone is not enough; you have to solve problems! Kaggle competitions are the best place for this. ✅ Classification problem for beginners ☑️ Regression-based challenge ✔️ Fake news detection with NLP ✔️ Deep learning on image data with TPU 📝 Complete list of competitions ⬅️Link https://t.me/CodeProgrammer 🌟