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Machine Learning

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 40 149 suscriptores, ocupando la posición 3 375 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 40 149 suscriptores.

Según los últimos datos del 28 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 378, y en las últimas 24 horas de 7, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.09%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.91% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 841 visualizaciones. En el primer día suele acumular 766 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 29 junio, 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.

40 149
Suscriptores
+724 horas
+1147 días
+37830 días
Archivo de publicaciones
📌 System Design: Load Balancer 🗂 Category: 🕒 Date: 2024-06-28 | ⏱️ Read time: 9 min read Orchestrating strategies for opti
📌 System Design: Load Balancer 🗂 Category: 🕒 Date: 2024-06-28 | ⏱️ Read time: 9 min read Orchestrating strategies for optimal workload distribution in microservice applications

📌 Demonstrating Prioritization Effectiveness in Sales 🗂 Category: 🕒 Date: 2024-06-28 | ⏱️ Read time: 6 min read The power
📌 Demonstrating Prioritization Effectiveness in Sales 🗂 Category: 🕒 Date: 2024-06-28 | ⏱️ Read time: 6 min read The power of machine learning for contact priorization

📌 5 Habits That Made Me A Data Scientist 🗂 Category: CODING 🕒 Date: 2024-06-28 | ⏱️ Read time: 7 min read Advice and tips
📌 5 Habits That Made Me A Data Scientist 🗂 Category: CODING 🕒 Date: 2024-06-28 | ⏱️ Read time: 7 min read Advice and tips on becoming a data scientist

📌 Different Ways of Image Generation with Stable Diffusion 3 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 8
📌 Different Ways of Image Generation with Stable Diffusion 3 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 8 min read Running SD3 in Google Colab and on a Local PC

📌 Modeling the Extinction of the Catalan Language 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 10 min read
📌 Modeling the Extinction of the Catalan Language 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 10 min read Applying existing literature to a practical case

📌 Using OpenAI and PandasAI for Series Operations 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-29 | ⏱️ Read time: 6
📌 Using OpenAI and PandasAI for Series Operations 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-29 | ⏱️ Read time: 6 min read Incorporate natural language queries and operations into your Python data cleaning workflow.

📌 Explainability, Interpretability and Observability in Machine Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-30 |
📌 Explainability, Interpretability and Observability in Machine Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-30 | ⏱️ Read time: 7 min read These are terms commonly used to describe the transparency of a model, but what do…

Over $20 BILLION wiped out, 1M+ traders erased in hours. Why did no one warn you? I switched from daily trading to arbitrage
Over $20 BILLION wiped out, 1M+ traders erased in hours. Why did no one warn you? I switched from daily trading to arbitrage right before the chaos—here’s the signal everyone’s missing. Are you ready to stop gambling? Find out how #ad InsideAds

📌 3 Essential Questions to Address When Building an API-Involved Incremental Data Loading Script 🗂 Category: DATA ENGINEERI
📌 3 Essential Questions to Address When Building an API-Involved Incremental Data Loading Script 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-06-30 | ⏱️ Read time: 9 min read This article explains both the conceptual framework and practical code implementation for syncing data from…

📌 Learn Transformer Fine-Tuning and Segment Anything 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-30 | ⏱️ Read time: 13 mi
📌 Learn Transformer Fine-Tuning and Segment Anything 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-30 | ⏱️ Read time: 13 min read Train Meta’s SAM to segment high fidelity masks for any domain

📌 Analyzing the Pros and Cons of Electric Vehicle Purchases: Insights from Newspaper News 🗂 Category: DATA SCIENCE 🕒 Date:
📌 Analyzing the Pros and Cons of Electric Vehicle Purchases: Insights from Newspaper News 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-01 | ⏱️ Read time: 10 min read In today’s market, buying electric cars represents an important challenge and a purchase decision that…

📌 Mastering SQL Optimization: From Functional to Efficient Queries 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-01 | ⏱️ Read t
📌 Mastering SQL Optimization: From Functional to Efficient Queries 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-01 | ⏱️ Read time: 11 min read Six Simple Yet Effective SQL Tips That Helped Me Reduce 50 Hours of Snowflake Query…

📌 Chart Wars: Pie Chart vs. Sorted Radial Bar Chart 🗂 Category: DATA VISUALIZATION 🕒 Date: 2024-07-01 | ⏱️ Read time: 8 mi
📌 Chart Wars: Pie Chart vs. Sorted Radial Bar Chart 🗂 Category: DATA VISUALIZATION 🕒 Date: 2024-07-01 | ⏱️ Read time: 8 min read Have your pie and eat it too!

📌 You Don’t Know Jacc(ard) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-01 | ⏱️ Read time: 11 min read When the Jaccard simila
📌 You Don’t Know Jacc(ard) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-01 | ⏱️ Read time: 11 min read When the Jaccard similarity index isn’t the right tool for the job, and what to…

📌 Framework for Success Metrics Questions | Facebook Groups Success Metrics 🗂 Category: META 🕒 Date: 2024-07-01 | ⏱️ Read
📌 Framework for Success Metrics Questions | Facebook Groups Success Metrics 🗂 Category: META 🕒 Date: 2024-07-01 | ⏱️ Read time: 6 min read The framework that will help you ace upcoming interviews

📌 Using a JSON Agent with LangChain, LangSmith and OpenAI’s GPT-4o 🗂 Category: 🕒 Date: 2024-07-01 | ⏱️ Read time: 9 min re
📌 Using a JSON Agent with LangChain, LangSmith and OpenAI’s GPT-4o 🗂 Category: 🕒 Date: 2024-07-01 | ⏱️ Read time: 9 min read Developing a chatbot to answer questions about a JSON dataset

📌 How to Turn Your AI Idea Into a Scalable Product: A Technical Guide 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-
📌 How to Turn Your AI Idea Into a Scalable Product: A Technical Guide 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-02 | ⏱️ Read time: 9 min read Time to leave localhost behind and start acquiring users

📌 Introduction to Linear Programming – Part II 🗂 Category: CODING 🕒 Date: 2024-07-02 | ⏱️ Read time: 16 min read Productio
📌 Introduction to Linear Programming – Part II 🗂 Category: CODING 🕒 Date: 2024-07-02 | ⏱️ Read time: 16 min read Production optimisation with R

📌 RFM Segmentation: Unleashing Customer Insights 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-02 | ⏱️ Read time: 9 min read Tr
📌 RFM Segmentation: Unleashing Customer Insights 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-02 | ⏱️ Read time: 9 min read Transforming customer data into actionable insights with RFM segmentation

📌 Continual Learning – A Deep Dive Into Elastic Weight Consolidation Loss 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-02 | ⏱️
📌 Continual Learning – A Deep Dive Into Elastic Weight Consolidation Loss 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-02 | ⏱️ Read time: 10 min read With PyTorch Implementation