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 347...

📈 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 40 273 suscriptores, ocupando la posición 3 347 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 40 273 suscriptores.

Según los últimos datos del 07 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 352, y en las últimas 24 horas de 21, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.23%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.88% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 896 visualizaciones. En el primer día suele acumular 758 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 08 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.

40 273

Suscriptores

+2124 horas

+957 días

+35230 días

896

Visitas de la publicación

~ 75824 horas

~ 1 03748 horas

2.23%

Tasa de compromiso

~ 2

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 277

📌 Learning ML or Learning About Learning ML? 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-03 | ⏱️ Read time: 4 min read Pragmatism versus (over-)planning

40 277

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40 277

📌 Statistical Learnability of Strategic Linear Classifiers: A Proof Walkthrough 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-01-08 | ⏱️ Read time: 19 min read With the help of an intricate geometric construction, we can prove that instance-wise cost functions…

40 277

📌 Advanced SQL Techniques for Unstructured Data Handling 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-08 | ⏱️ Read time: 7 min read Everything you need to know to get started with text mining

40 277

📌 Missing Data in Time-Series? Machine Learning Techniques (Part 2) 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-01-08 | ⏱️ Read time: 12 min read Using Clustering Algorithms to Handle Missing Time-Series Data

40 277

📌 Speed Up PyTorch With Custom Kernels. But It Gets Progressively Darker 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-01-09 | ⏱️ Read time: 5 min read We’ll begin with torch.compile, move on to writing a custom Triton kernel, and finally dive…

40 277

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40 277

📌 Jingle Bells and Statistical Tests 🗂 Category: STATISTICS 🕒 Date: 2024-12-25 | ⏱️ Read time: 8 min read Data Types, Hypotheses and Statistical Tests That Fit Them with Festive Christmas Market Examples

40 277

📌 Understanding When and How to Implement FastAPI Middleware (Examples and Use Cases) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-12-25 | ⏱️ Read time: 4 min read Supercharge Your FastAPI with Middleware: Practical Use Cases and Examples

40 277

📌 Training LLM, from Scratch, in Rust 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-12-26 | ⏱️ Read time: 16 min read In this companion article, I’ll show my implementation for training from scratch a GPT-like model,…

40 277

📌 Calculating a linear extrapolation (or Trend) in DAX 🗂 Category: 🕒 Date: 2024-12-26 | ⏱️ Read time: 10 min read In DAX there is no built-in method to calculate a Trend. Therefore we must do…

40 277

📌 Your Company Needs Small Language Models 🗂 Category: CHATGPT 🕒 Date: 2024-12-26 | ⏱️ Read time: 15 min read When specialized models outperform general-purpose models

40 277

📌 Linearizing Attention 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-12-26 | ⏱️ Read time: 8 min read Breaking the Quadratic Barrier: Modern Alternatives to Softmax Attention

40 277

📌 How Neural Networks Learn: A Probabilistic Viewpoint 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-12-26 | ⏱️ Read time: 8 min read Understanding Loss Functions in Training Neural Networks

40 277

📌 Track Computer Vision Experiments with MLflow 🗂 Category: 🕒 Date: 2024-12-26 | ⏱️ Read time: 10 min read Discover how to set up an efficient MLflow environment to track your experiments, compare and…

40 277

📌 Lessons from COVID-19: Why Probability Distributions Matter 🗂 Category: COVID-19 🕒 Date: 2024-12-27 | ⏱️ Read time: 13 min read Understanding Distributions with Extremes: Probability for Data Science Series (END)

40 277

📌 Understanding the Optimization Process Pipeline in Linear Programming 🗂 Category: 🕒 Date: 2024-12-27 | ⏱️ Read time: 8 min read An introduction to the backend and frontend processes in linear programming, including the mathematical programming…

40 277

📌 Master Bots Before Starting with AI Agents: Simple Steps to Create a Mastodon Bot with Python 🗂 Category: PROGRAMMING 🕒 Date: 2024-12-27 | ⏱️ Read time: 13 min read I recently published a post on Mastodon that was shared by six other accounts within…

40 277

📌 Measuring Cross-Product Adoption Using dbt_set_similarity 🗂 Category: SQL 🕒 Date: 2024-12-28 | ⏱️ Read time: 5 min read Enhancing cross-product insights within dbt workflows

40 277

📌 Deep Dive into Multithreading, Multiprocessing, and Asyncio 🗂 Category: 🕒 Date: 2024-12-28 | ⏱️ Read time: 10 min read How to choose the right concurrency model