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 Siria227 Tecnologías y Aplicaciones3 375...

📈 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

841

Visitas de la publicación

~ 76624 horas

~ 1 08948 horas

2.09%

Tasa de compromiso

~ 3

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 152

📌 EDA for Word Embeddings 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-12 | ⏱️ Read time: 16 min read Data scientists use EDA for everything. Why not word embeddings?

40 152

📌 Gower’s Distance for Mixed Categorical and Numerical Data 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-12 | ⏱️ Read time: 8 min read A distance measure for mixed data that can be used for clustering

40 152

🤖🧠 ROMA: The Ultimate AI Framework That Lets You Build High-Performance Agents in Minutes 🗓️ 11 Oct 2025 📚 AI News & Trends Artificial Intelligence continues to evolve at an unprecedented pace, with agent-based frameworks becoming increasingly important for tackling complex problems. ROMA (Recursive Open Meta-Agents) represents a significant leap forward in this space, providing developers and researchers with a hierarchical, flexible, and high-performance framework for building multi-agent AI systems. This article explores ROMA’s architecture, technical capabilities, practical ... #ROMA #AIFramework #MultiAgentSystems #ArtificialIntelligence #HighPerformanceAI #AgentBasedAI

40 152

📌 A Practical Framework for Search Evaluation 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-12 | ⏱️ Read time: 15 min read A Data-Driven Approach to Elevating User Experience and Business Performance with Search

40 152

📌 Multi-Headed Self Attention – By Hand 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-12 | ⏱️ Read time: 5 min read Hand computing the cornerstone of modern AI.

40 152

📌 Predictive Marketing Mix Modeling with GLOP: The Perfect Cocktail Shaker 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-07-12 | ⏱️ Read time: 12 min read Maximizing profit using ML and GLOP (by Google) in the digital landscape

40 152

📌 Deliver Your Data as a Product, But Not as an Application 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-07-12 | ⏱️ Read time: 11 min read Data as a product is an intriguing concept, but beware of the application trap

40 152

🤖🧠 How oLLM Makes Large-Context AI Models Run Smoothly on 8GB GPUs 🗓️ 11 Oct 2025 📚 AI News & Trends Artificial intelligence has revolutionized the way we process information, analyze data, and automate complex tasks. With the rise of large language models (LLMs), AI capabilities have grown exponentially, enabling applications from natural language understanding to multimodal reasoning. However, running these models efficiently especially with massive context windows, remains a challenge due to their high memory ... #oLLM #LargeContextAI #AIGPU #MachineLearning #LLMs #AIOptimization

40 152

📌 Rainbow: The Colorful Evolution of Deep Q-Networks 🗂 Category: DEEP LEARNING 🕒 Date: 2024-07-12 | ⏱️ Read time: 20 min read Everything you need to assemble the DQN Megazord in JAX.

40 152

📌 Time Series Are Not That Different for LLMs 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-12 | ⏱️ Read time: 8 min read Harnessing the power of LLMs for time series modeling

40 152

📌 Lessons Learned as a Data Science Manager and Why I’m Moving Back to an Individual Contributor Role 🗂 Category: CAREER ADVICE 🕒 Date: 2024-07-13 | ⏱️ Read time: 11 min read The three questions I asked myself that helped me pick my career path

40 152

📌 How to Deliver Successful Data Science Consulting Projects 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-13 | ⏱️ Read time: 11 min read Key recommendations for how to succeed with data science consulting projects and build lasting client…

40 152

🤖🧠 Gamma PPT AI : Unlock Presentations in Minutes 🗓️ 10 Oct 2025 📚 AI News & Trends In today’s fast-paced world, creating high-impact presentations can be a tedious, time-consuming process especially when you need beautiful visuals, crisp content and consistent branding. That’s where Gamma PPT AI comes in. It’s a tool that promises to transform how we make slide decks by letting AI handle design, layout and content generation. In this blog, ... #GammaPPTAI #AIPresentations #PresentationTools #ArtificialIntelligence #DesignAutomation #SlideDeck

40 152

📌 Why It Feels Impossible to Get a Data Science Job 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-13 | ⏱️ Read time: 10 min read Reasons why the market is tough and what you can do about it

40 152

📌 Reinforcement Learning, Part 5: Temporal-Difference Learning 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-13 | ⏱️ Read time: 18 min read Intelligently synergizing dynamic programming and Monte Carlo algorithms

40 152

📌 Essential Considerations for Implementing Machine Learning 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-13 | ⏱️ Read time: 8 min read Is your use case a viable ML product from a traditional ML and production perspective?

40 152

📌 Three reasons why developers should use DuckDB 🗂 Category: SQL 🕒 Date: 2024-07-14 | ⏱️ Read time: 5 min read Developers often have to analyse data, e.g. assessing the impact of an outage. DuckDB is…

40 152

🤖🧠 PyMuPDF: The Ultimate Python Library for High-Performance PDF Processing 🗓️ 09 Oct 2025 📚 AI News & Trends If you’re a Python developer working with PDF documents whether it’s for text extraction, data analysis conversion or annotation then you’ve likely encountered the limitations of traditional tools. That’s where PyMuPDF also known as fitz, shines. It’s a lightweight, high-performance Python library that enables comprehensive PDF manipulation with minimal dependencies and maximum flexibility. In this ... #PyMuPDF #PythonLibrary #PDFProcessing #TextExtraction #DataAnalysis #HighPerformance

40 152

📌 LLM Agents Demystified 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-14 | ⏱️ Read time: 16 min read Hands-on ReAct agent implementation with AdalFlow library

40 152

📌 Chaining Pandas Operations: Strengths and Limitations 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-15 | ⏱️ Read time: 20 min read Learn when it’s worth chaining Pandas operations in pipes.