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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

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📈 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 40 251 suscriptores, ocupando la posición 3 343 en la categoría Tecnologías y Aplicaciones y el puesto 227 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 251 suscriptores.

Según los últimos datos del 05 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 346, y en las últimas 24 horas de 22, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.97%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.86% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 794 visualizaciones. En el primer día suele acumular 749 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 06 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.

40 251
Suscriptores
+2224 horas
+987 días
+34630 días
Archivo de publicaciones
📌 Python Can Now Call Mojo 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-21 | ⏱️ Read time: 14 min read Boost your runtimes with
📌 Python Can Now Call Mojo 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-21 | ⏱️ Read time: 14 min read Boost your runtimes with lightning-fast Mojo code

📌 Data Visualization Explained: What It Is and Why It Matters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-21 | ⏱️ Read time:
📌 Data Visualization Explained: What It Is and Why It Matters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-21 | ⏱️ Read time: 8 min read A brief introduction to data visualization and its importance in today’s technological landscape.

📌 Building a Local Voice Assistant with LLMs and Neural Networks on Your CPU Laptop 🗂 Category: DATA SCIENCE 🕒 Date: 2024-
📌 Building a Local Voice Assistant with LLMs and Neural Networks on Your CPU Laptop 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-19 | ⏱️ Read time: 6 min read A practical guide to run lightweight LLMs using python

📌 3 Triangle-Shaped Chart Ideas as Alternatives to Some Basic Charts 🗂 Category: DATA VISUALIZATION 🕒 Date: 2024-11-19 | ⏱
📌 3 Triangle-Shaped Chart Ideas as Alternatives to Some Basic Charts 🗂 Category: DATA VISUALIZATION 🕒 Date: 2024-11-19 | ⏱️ Read time: 8 min read Creating data visualizations with Python as alternatives to bar charts, pie charts, and some 3D…

📌 How I Created a Data Science Project Following CRISP-DM Lifecycle 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-13 | ⏱️ Read
📌 How I Created a Data Science Project Following CRISP-DM Lifecycle 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-13 | ⏱️ Read time: 26 min read An end-to-end project using the CRISP-DM framework

📌 Awesome Plotly with Code Series (Part 4): Grouping Bars vs Multi-Coloured Bars 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-
📌 Awesome Plotly with Code Series (Part 4): Grouping Bars vs Multi-Coloured Bars 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-14 | ⏱️ Read time: 13 min read Do technicolour bars really help make a story clear?

📌 Writing LLMs in Rust: Looking for an Efficient Matrix Multiplication 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11
📌 Writing LLMs in Rust: Looking for an Efficient Matrix Multiplication 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-14 | ⏱️ Read time: 16 min read Here are the lessons I learned and how I am writing llm.rust and tackling the…

📌 How To Up-Skill In Data Science 🗂 Category: CAREER ADVICE 🕒 Date: 2024-11-14 | ⏱️ Read time: 7 min read My framework for
📌 How To Up-Skill In Data Science 🗂 Category: CAREER ADVICE 🕒 Date: 2024-11-14 | ⏱️ Read time: 7 min read My framework for continually becoming a better data scientist

📌 Network Analysis, Diffusion Models, Data Lakehouses, and More: Our Best Recent Deep Dives 🗂 Category: DATA SCIENCE 🕒 Dat
📌 Network Analysis, Diffusion Models, Data Lakehouses, and More: Our Best Recent Deep Dives 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-14 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

📌 Why STEM Is Important for Any Data Scientist 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-14 | ⏱️ Read time: 8 min read 3 ca
📌 Why STEM Is Important for Any Data Scientist 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-14 | ⏱️ Read time: 8 min read 3 cases to prove this from my own experience

📌 Gradient Boosting Regressor, Explained: A Visual Guide with Code Examples 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-1
📌 Gradient Boosting Regressor, Explained: A Visual Guide with Code Examples 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-14 | ⏱️ Read time: 14 min read Fitting to errors one booster stage at a time

📌 Techniques for Chat Data Analytics with Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-15 | ⏱️ Read time: 11 min read P
📌 Techniques for Chat Data Analytics with Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-15 | ⏱️ Read time: 11 min read Part II: Topic Extraction with BERTopic

📌 Rewiring My Career: How I Transitioned from Electrical Engineering to Data Engineering 🗂 Category: DATA ENGINEERING 🕒 Da
📌 Rewiring My Career: How I Transitioned from Electrical Engineering to Data Engineering 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-11-15 | ⏱️ Read time: 12 min read Data is booming and so are the job opportunities in this field. A must read…

📌 Field Boundary Detection in Satellite Imagery Using the SAM2 Model 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-15 | ⏱️ Read
📌 Field Boundary Detection in Satellite Imagery Using the SAM2 Model 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-15 | ⏱️ Read time: 14 min read Step-by-Step Tutorial on Applying Segment Anything Model Version 2 to Satellite Imagery for Detecting and…

📌 ROI Worship Can Be Bad For Business 🗂 Category: BUSINESS 🕒 Date: 2024-11-15 | ⏱️ Read time: 8 min read Watch out for the
📌 ROI Worship Can Be Bad For Business 🗂 Category: BUSINESS 🕒 Date: 2024-11-15 | ⏱️ Read time: 8 min read Watch out for these three ways too much of a good thing can be dangerous

📌 Introduction to the Finite Normal Mixtures in Regression with 🗂 Category: 🕒 Date: 2024-11-15 | ⏱️ Read time: 8 min read
📌 Introduction to the Finite Normal Mixtures in Regression with 🗂 Category: 🕒 Date: 2024-11-15 | ⏱️ Read time: 8 min read In this post, we demonstrate how to simulate a finite mixture model for regression using…

📌 Why Most Cross-Validation Visualizations Are Wrong (And How to Fix Them) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-16 | ⏱
📌 Why Most Cross-Validation Visualizations Are Wrong (And How to Fix Them) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-16 | ⏱️ Read time: 12 min read Stop using moving boxes!

📌 Open the Artificial Brain: Sparse Autoencoders for LLM Inspection 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-16
📌 Open the Artificial Brain: Sparse Autoencoders for LLM Inspection 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-16 | ⏱️ Read time: 15 min read A deep dive into LLM visualization and interpretation using sparse autoencoders

📌 Exploring Music Transcription with Multi-Modal Language Models 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-17 |
📌 Exploring Music Transcription with Multi-Modal Language Models 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-17 | ⏱️ Read time: 21 min read Using Qwen2-Audio to transcribe music into sheet music

📌 Spoiler Alert: The Magic of RAG Does Not Come from AI 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-17 | ⏱️ Read time: 10
📌 Spoiler Alert: The Magic of RAG Does Not Come from AI 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-17 | ⏱️ Read time: 10 min read Why retrieval, not generation, makes RAG systems magical

Machine Learning - Estadísticas y analítica del canal de Telegram @machinelearning9