Machine Learning

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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Red:Machine Learning with Python Siria228 Tecnologías y Aplicaciones3 352...

📈 Análisis del canal de Telegram Machine Learning

El canal Machine Learning (@machinelearning9) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 205 suscriptores, ocupando la posición 3 352 en la categoría Tecnologías y Aplicaciones y el puesto 228 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 205 suscriptores.

Según los últimos datos del 02 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 343, 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 1.99%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.28% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 800 visualizaciones. En el primer día suele acumular 915 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
Intereses temáticos: El contenido se centra en temas clave como distance, insidead, gpu, learning, degree.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 03 julio, 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 Tecnologías y Aplicaciones.

40 205

Suscriptores

+1024 horas

+837 días

+34330 días

800

Visitas de la publicación

~ 91524 horas

~ 1 23548 horas

1.99%

Tasa de compromiso

~ 3

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 210

📌 TimesFM: The Boom of Foundation Models in Time Series Forecasting 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-20 | ⏱️ Read time: 14 min read Explore How Google’s Latest AI Model Delivers Zero-Shot Forecasting Accuracy Using Over 307 Billion Data…

40 210

📌 Topic Modelling Your Personal Data 🗂 Category: 🕒 Date: 2024-09-21 | ⏱️ Read time: 29 min read Using Traditional and Transformer Models to Explore Personal Data Stored by Brokers

40 210

📌 Reinforcement Learning, Part 8: Feature State Construction 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-21 | ⏱️ Read time: 17 min read Enhancing linear methods by smartly incorporating state features into the learning objective

40 210

“Nobody believed you could grow small capital—until I saw this.” $1,000 turned into real profit before my eyes. The secret? Bonus fuel & copytrading with Elite Gold. Want proof? See how it’s actually done before the bonus ends. #ad InsideAds

40 210

📌 A Basic Introduction to Quantum GANs 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read “Quantum computing just becomes vastly simpler once you take the physics out of it.”

40 210

📌 An Intuitive Guide to Integrate SQL and Python for Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read Learn to master MySQL connector, a Python library that enables to interact with MYSQL database

40 210

📌 Proxy SHAP: Speed Up Explainability with Simpler Models 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-21 | ⏱️ Read time: 7 min read A Practical Guide to Efficient SHAP Computation

40 210

📌 The Machine Learning Lessons I’ve Learned This Month 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-30 | ⏱️ Read time: 7 min read September 2025: library or self-made, Ditto and Launchbar, reading widely and deeply

40 210

📌 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

40 210

📌 Actual Intelligence in the Age of AI 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2025-09-30 | ⏱️ Read time: 11 min read Jarom Hulet on mastering fundamentals, hiring well, and deciding what to write about next

40 210

📌 Beyond ROC-AUC and KS: The Gini Coefficient, Explained Simply 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-30 | ⏱️ Read time: 7 min read Understanding Gini and Lorenz curves for smarter model evaluation

40 210

Repost from Machine Learning with Python

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

40 210

Ever wondered why the same grape can taste wildly different from one bottle to another? The answer lies in the secrets of terroir, winemaking, and those rare finds only true wine lovers discover. Unlock a world of honest reviews, tasting notes, and hidden gems—subscribe to Simply Wine | Great Wine Lover and turn every glass into a new adventure! #ad InsideAds

40 210

📌 Hands-On Numerical Derivative with Python, from Zero to Hero 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-22 | ⏱️ Read time: 10 min read Here’s everything you need to know (beyond the standard definition) to master the numerical derivative…

40 210

📌 How I Deal with Hallucinations at an AI Startup 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-22 | ⏱️ Read time: 8 min read And the difference between weak vs strong grounding

40 210

📌 Data Empowers Business 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-09-22 | ⏱️ Read time: 10 min read Exploiting the full potential of universal data supply

40 210

📌 Build Your Agents from Scratch 🗂 Category: 🕒 Date: 2024-09-23 | ⏱️ Read time: 8 min read Design your own agents without any framework

40 210

📌 Embeddings Are Kind of Shallow 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-09-23 | ⏱️ Read time: 33 min read What I learned doing semantic search on U.S. Presidents with four language model embeddings

40 210

📌 Programming an Arduino with CrewAI Agents 🗂 Category: PROGRAMMING 🕒 Date: 2024-09-23 | ⏱️ Read time: 7 min read An interaction between electronics and LLMs

40 210

📌 Breaking It Down : Chunking Techniques for Better RAG 🗂 Category: 🕒 Date: 2024-09-23 | ⏱️ Read time: 19 min read Mastering chunking for efficient retrieval in RAG systems