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 329...

📈 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 40 346 suscriptores, ocupando la posición 3 329 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 40 346 suscriptores.

Según los últimos datos del 11 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 393, y en las últimas 24 horas de 17, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.29%. 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 924 visualizaciones. En el primer día suele acumular 702 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 12 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.

40 346

Suscriptores

+1724 horas

+1237 días

+39330 días

924

Visitas de la publicación

~ 70224 horas

~ 1 07048 horas

2.29%

Tasa de compromiso

~ 2

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 365

📌 Time Series Forecasting Made Simple (Part 3.1): STL Decomposition 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-09 | ⏱️ Read time: 24 min read STL Decomposition excels when seasonal patterns evolve over time.

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📌 How to Perform Effective Data Cleaning for Machine Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-09 | ⏱️ Read time: 11 min read Learn how you can improve your machine learning models using effective data cleaning

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📌 AI Agents Are Shaping the Future of Work Task by Task, Not Job by Job 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-09 | ⏱️ Read time: 12 min read What two groundbreaking studies reveal about the future of human-AI collaboration, and the enterprise playbook…

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📌 Recap of all types of LLM Agents 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-07-09 | ⏱️ Read time: 6 min read Regular, ReAct, Chain-of-Thought, Reflexion, ToT, GoT, PoT

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📌 Work Data Is the Next Frontier for GenAI 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-07-09 | ⏱️ Read time: 17 min read 9 reasons why work data is the single most valuable data source for LLM training,…

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📌 The Crucial Role of NUMA Awareness in High-Performance Deep Learning 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-10 | ⏱️ Read time: 16 min read PyTorch model performance analysis and optimization — Part 10

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📌 Worried About AI? Use It to Your Advantage 🗂 Category: THE VARIABLE 🕒 Date: 2025-07-10 | ⏱️ Read time: 3 min read This week, we focus on the future of data science and the opportunities that can…

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📌 Evaluation-Driven Development for LLM-Powered Products: Lessons from Building in Healthcare 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-07-10 | ⏱️ Read time: 30 min read How metrics and monitoring combine with human expertise to build trustworthy AI in healthcare.

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📌 Scene Understanding in Action: Real-World Validation of Multimodal AI Integration 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-10 | ⏱️ Read time: 13 min read A deep dive into real-world case studies: from indoor space and urban streets to world-famous…

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📌 Reducing Time to Value for Data Science Projects: Part 3 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-10 | ⏱️ Read time: 14 min read Setting up a robust experimentation process

40 365

📌 Building a Сustom MCP Chatbot 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-10 | ⏱️ Read time: 25 min read Understanding all the details of the model context protocol

40 365

📌 Hitchhiker’s Guide to RAG: From Tiny Files to Tolstoy with OpenAI’s API and LangChain 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-07-11 | ⏱️ Read time: 9 min read Scaling a simple RAG pipeline from simple notes to full books

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📌 Are You Being Unfair to LLMs? 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-07-11 | ⏱️ Read time: 9 min read They may deserve better.

40 365

📌 Let AI Tune Your Voice Assistant 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-14 | ⏱️ Read time: 29 min read A practical guide to automating prompt engineering for voice assistants

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📌 The Age of Self-Evolving AI Is Here 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-07-17 | ⏱️ Read time: 17 min read How Meta’s latest breakthrough lets models learn, adapt, and improve — all on their own

40 365

Repost from Machine Learning with Python

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

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📌 Tracking Drill-Through Actions on Power BI Report Titles 🗂 Category: POWER BI 🕒 Date: 2025-07-14 | ⏱️ Read time: 6 min read When you have a drill-through page that can be called from multiple pages, it could…

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📌 CLIP Model Overview : Unlocking the Power of Multimodal AI 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-14 | ⏱️ Read time: 7 min read The magic behind multimodal models unlocked through contrastive learning

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📌 Simple Guide to Multi-Armed Bandits: A Key Concept Before Reinforcement Learning 🗂 Category: REINFORCEMENT LEARNING 🕒 Date: 2025-07-14 | ⏱️ Read time: 12 min read How AI learns to make better decisions and why you should care about exploration vs.…

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📌 Dynamic Inventory Optimization with Censored Demand 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-14 | ⏱️ Read time: 20 min read A sequential decision framework with Bayesian learning