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 Siria225 Tecnologías y Aplicaciones3 327...

📈 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 40 373 suscriptores, ocupando la posición 3 327 en la categoría Tecnologías y Aplicaciones y el puesto 225 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 373 suscriptores.

Según los últimos datos del 12 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 399, 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 2.42%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.74% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 979 visualizaciones. En el primer día suele acumular 703 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 4.
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 13 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.

40 373

Suscriptores

+2424 horas

+1257 días

+39930 días

979

Visitas de la publicación

~ 70324 horas

~ 95648 horas

2.42%

Tasa de compromiso

~ 2

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 373

📌 Why Science Must Embrace Co-Creation with Generative AI to Break Current Research Barriers 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-08-25 | ⏱️ Read time: 24 min read An Open Letter to the Scientific Community

40 373

📌 How to Benchmark Classical Machine Learning Workloads on Google Cloud 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-25 | ⏱️ Read time: 8 min read Harnessing CPUs for Practical, Cost-Effective Machine Learning

40 373

📌 Why Your Prompts Don’t Belong in Git 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-25 | ⏱️ Read time: 5 min read The hidden cost of storing prompts in your source code

40 373

📌 LLM Monitoring and Observability: Hands-on with Langfuse 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-25 | ⏱️ Read time: 22 min read Learn the fundamentals of LLM monitoring and observability, from tracing to evaluation and setting up…

40 373

📌 Google’s URL Context Grounding: Another Nail in RAG’s Coffin? 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-26 | ⏱️ Read time: 13 min read Google’s hot streak in AI-related releases continues unabated. Just a few days ago, it released…

40 373

📌 Using Google’s LangExtract and Gemma for Structured Data Extraction 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-26 | ⏱️ Read time: 9 min read Extracting structured information effectively and accurately from long unstructured text with LangExtract and LLMs

40 373

📌 Plato’s Cave and the Shadows of Data 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-26 | ⏱️ Read time: 4 min read On truth, illusion, and the limits of what data can reveal

40 373

📌 How to Develop Powerful Internal LLM Benchmarks 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-26 | ⏱️ Read time: 7 min read Learn how to compare LLMs using your own interal benchmark

40 373

📌 The Math You Need to Pan and Tilt 360° Images 🗂 Category: MATH 🕒 Date: 2025-08-27 | ⏱️ Read time: 12 min read Panning a spherical image is just a horizontal roll, but tilting it vertically is much…

40 373

📌 A Brief History of GPT Through Papers 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-27 | ⏱️ Read time: 16 min read Language models are becoming really good. But where did they come from?

40 373

📌 Time Series Forecasting Made Simple (Part 4.1): Understanding Stationarity in a Time Series 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-27 | ⏱️ Read time: 11 min read An intuitive guide to stationarity in a time series

40 373

📌 Everything I Studied to Become a Machine Learning Engineer (No CS Background) 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-27 | ⏱️ Read time: 9 min read The books, courses, and resources I used in my journey.

40 373

📌 Get AI-Ready: How to Prepare for a World of Agentic AI as Tech Professionals 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-08-27 | ⏱️ Read time: 6 min read Explore how Agentic AI is reshaping the tech careers, from data to decision-making, and how…

40 373

📌 Air for Tomorrow: Why Openness in Air Quality Research and Implementation Matters for Global Equity 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-27 | ⏱️ Read time: 10 min read Understand how open source can help you unravel air quality

40 373

📌 August Must-Reads: LLM Costs, Research Agents, and More 🗂 Category: THE VARIABLE 🕒 Date: 2025-08-28 | ⏱️ Read time: 2 min read Our most-read and -shared stories of the past month

40 373

📌 A Visual Guide to Tuning Decision-Tree Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-28 | ⏱️ Read time: 11 min read How hyperparameter tuning visually changes decision trees

40 373

📌 Graph Coloring for Data Science: A Comprehensive Guide 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-28 | ⏱️ Read time: 11 min read From theoretical puzzles to practical applications

40 373

📌 Stepwise Selection Made Simple: Improve Your Regression Models in Python 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-28 | ⏱️ Read time: 21 min read Dimensionality reduction in linear regression: classical stepwise methods and a Python application on real-world data

40 373

📌 Implementing the Hangman Game in Python 🗂 Category: PROGRAMMING 🕒 Date: 2025-08-28 | ⏱️ Read time: 11 min read A beginner-friendly project to understand variables, loops, and conditions in Python

40 373

📌 How to Import Pre-Annotated Data into Label Studio and Run the Full Stack with Docker 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-29 | ⏱️ Read time: 9 min read From VOC to JSON: Importing pre-annotations made simple