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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 40 229 suscriptores, ocupando la posición 3 336 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 40 229 suscriptores.

Según los últimos datos del 04 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 16, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.92%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.89% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 771 visualizaciones. En el primer día suele acumular 761 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 05 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.

40 229
Suscriptores
+1624 horas
+837 días
+34330 días
Archivo de publicaciones
📌 Universal Data Supply: Know Your Business 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-22 | ⏱️ Read time: 10 min read An
📌 Universal Data Supply: Know Your Business 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-22 | ⏱️ Read time: 10 min read An industry example to emphasize the importance of understanding your business case

📌 Image Data Collection for Climate Change Analysis 🗂 Category: CLIMATE CHANGE 🕒 Date: 2024-10-22 | ⏱️ Read time: 9 min re
📌 Image Data Collection for Climate Change Analysis 🗂 Category: CLIMATE CHANGE 🕒 Date: 2024-10-22 | ⏱️ Read time: 9 min read A beginner’s guide

📌 Comprehensive Guide to Crafting a Perfect CV in Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-22 | ⏱️ Read time:
📌 Comprehensive Guide to Crafting a Perfect CV in Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-22 | ⏱️ Read time: 22 min read Impress recruiters and land your dream job by creating a standout resume

📌 An Introduction to Using PCA for Outlier Detection 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-22 | ⏱️ Read time: 18 mi
📌 An Introduction to Using PCA for Outlier Detection 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-22 | ⏱️ Read time: 18 min read A surprisingly effective means to identify outliers in numeric data

📌 Mastering Back-of-the-Envelope Math Will Make You a Better Data Scientist 🗂 Category: ANALYTICS 🕒 Date: 2024-10-23 | ⏱️
📌 Mastering Back-of-the-Envelope Math Will Make You a Better Data Scientist 🗂 Category: ANALYTICS 🕒 Date: 2024-10-23 | ⏱️ Read time: 14 min read A quick and dirty answer is often more helpful than a fancy model

📌 ML Metamorphosis: Chaining ML Models for Optimized Results 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-23 | ⏱️ Read time: 8
📌 ML Metamorphosis: Chaining ML Models for Optimized Results 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-23 | ⏱️ Read time: 8 min read The universal principle of knowledge distillation, model compression, and rule extraction

📌 Time Series – From Analyzing the Past to Predicting the Future 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-23 | ⏱️ Read tim
📌 Time Series – From Analyzing the Past to Predicting the Future 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-23 | ⏱️ Read time: 22 min read How to learn from the past with time series.

📌 How AlphaFold 3 Is Like DALLE 2 and Other Learnings 🗂 Category: 🕒 Date: 2024-10-24 | ⏱️ Read time: 7 min read Understand
📌 How AlphaFold 3 Is Like DALLE 2 and Other Learnings 🗂 Category: 🕒 Date: 2024-10-24 | ⏱️ Read time: 7 min read Understanding AI applications in bio for machine learning engineers

📌 Are you Aware of the Potential of Your Data Expertise in Driving Business Profitability? 🗂 Category: ANALYTICS 🕒 Date: 2
📌 Are you Aware of the Potential of Your Data Expertise in Driving Business Profitability? 🗂 Category: ANALYTICS 🕒 Date: 2024-10-24 | ⏱️ Read time: 12 min read A reflection of a supply chain data scientist who randomly discovered the power of data…

📌 Transforming Data Quality: Automating SQL Testing for Faster, Smarter Analytics 🗂 Category: SQL 🕒 Date: 2024-10-26 | ⏱️
📌 Transforming Data Quality: Automating SQL Testing for Faster, Smarter Analytics 🗂 Category: SQL 🕒 Date: 2024-10-26 | ⏱️ Read time: 13 min read How to test the quality of SQL and resultant dataset against the business question to…

📌 Awesome Plotly with Code Series (Part 2): Colouring Bar Charts 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-26 | ⏱️ Read tim
📌 Awesome Plotly with Code Series (Part 2): Colouring Bar Charts 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-26 | ⏱️ Read time: 10 min read Don’t create a rainbow coloured bar chart. But don’t make your bar charts boring either

📌 Oversampling and Undersampling, Explained: A Visual Guide with Mini 2D Dataset 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-
📌 Oversampling and Undersampling, Explained: A Visual Guide with Mini 2D Dataset 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-26 | ⏱️ Read time: 11 min read Artificially generating and deleting data for the greater good

📌 Gen-AI Safety Landscape: A Guide to the Mitigation Stack for Text-to-Image Models 🗂 Category: 🕒 Date: 2024-10-26 | ⏱️ Re
📌 Gen-AI Safety Landscape: A Guide to the Mitigation Stack for Text-to-Image Models 🗂 Category: 🕒 Date: 2024-10-26 | ⏱️ Read time: 15 min read No Wild West for AI: A tour of the safety components that tame T2I models

📌 Learnings from My First Year of Being a Data Analyst 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-26 | ⏱️ Read time: 7 min r
📌 Learnings from My First Year of Being a Data Analyst 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-26 | ⏱️ Read time: 7 min read Insights on dealing with statistics, interacting with people, and maximizing productivity at the workplace

📌 Untangling AI systems 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-26 | ⏱️ Read time: 16 min read How physics can help u
📌 Untangling AI systems 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-26 | ⏱️ Read time: 16 min read How physics can help us understand neural networks

📌 Understanding K-Fold Target Encoding to Handle High Cardinality 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-26 | ⏱️ Rea
📌 Understanding K-Fold Target Encoding to Handle High Cardinality 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-26 | ⏱️ Read time: 7 min read Balancing complexity and performance: An in-depth look at K-fold target encoding

📌 Why Are Marketers Turning To Quasi Geo-Lift Experiments? (And How to Plan Them) 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09
📌 Why Are Marketers Turning To Quasi Geo-Lift Experiments? (And How to Plan Them) 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-23 | ⏱️ Read time: 22 min read Are “quasi” geo-lift experiments the missing piece for your marketing science function?

📌 Generative AI Myths, Busted: An Engineers’s Quick Guide 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-23 | ⏱️ Read
📌 Generative AI Myths, Busted: An Engineers’s Quick Guide 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-23 | ⏱️ Read time: 11 min read A super simple and quick guide to how generative AI works, the myths around it,…

📌 The Art of Asking Good Questions 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-23 | ⏱️ Read time: 7 min read As a data scient
📌 The Art of Asking Good Questions 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-23 | ⏱️ Read time: 7 min read As a data scientist, are you driving product decisions? Or just supporting them? The right…

📌 Generating Consistent Imagery with Gemini 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-09-23 | ⏱️ Read time: 19 min read A
📌 Generating Consistent Imagery with Gemini 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-09-23 | ⏱️ Read time: 19 min read A practical guide to building a prompt-based generation pipeline for your image library