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

40 346

📌 Applications of Density Estimation to Legal Theory 🗂 Category: DATA SCIENCE 🕒 Date: 2025-06-10 | ⏱️ Read time: 15 min read A brief analysis using density estimation to compare the two-verdict and three-verdict systems.

40 346

📌 10,000x Faster Bayesian Inference: Multi-GPU SVI vs. Traditional MCMC 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-10 | ⏱️ Read time: 18 min read Using GPU acceleration to speed up Bayesian Inference from months to minutes…

40 346

📌 Automate Models Training: An MLOps Pipeline with Tekton and Buildpacks 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-10 | ⏱️ Read time: 11 min read A step-by-step guide to containerizing and orchestrating an ML training workflow without the Dockerfile headache,…

40 346

📌 Audio Spectrogram Transformers Beyond the Lab 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-10 | ⏱️ Read time: 7 min read A recipe for building a portable soundscape monitoring app with AudioMoth, Raspberry Pi, and a…

40 346

📌 Mobile App Development with Python 🗂 Category: PROGRAMMING 🕒 Date: 2025-06-11 | ⏱️ Read time: 8 min read Build iOS & Android Apps with Kivy

40 346

📌 Can AI Truly Develop a Memory That Adapts Like Ours? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-12 | ⏱️ Read time: 17 min read Exploring Titans: A new architecture equipping LLMs with human-inspired memory that learns and updates itself…

40 346

📌 Exploring the Proportional Odds Model for Ordinal Logistic Regression 🗂 Category: DATA SCIENCE 🕒 Date: 2025-06-12 | ⏱️ Read time: 21 min read Understanding and Implementing Brant’s Tests in Ordinal Logistic Regression with Python

40 346

📌 User Authorisation in Streamlit With OIDC and Google 🗂 Category: DATA SCIENCE 🕒 Date: 2025-06-12 | ⏱️ Read time: 10 min read Log in to a Streamlit app with a Google email account

40 346

📌 Design Smarter Prompts and Boost Your LLM Output: Real Tricks from an AI Engineer’s Toolbox 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-12 | ⏱️ Read time: 9 min read Not just what you ask, but how you ask it. Practical techniques for prompt engineering…

40 346

📌 Agentic AI 103: Building Multi-Agent Teams 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-12 | ⏱️ Read time: 9 min read Build multi-agent teams that can automate tasks and enhance productivity.

40 346

📌 Connecting the Dots for Better Movie Recommendations 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-12 | ⏱️ Read time: 11 min read Connecting the Dots for Better Movie Recommendations: Lightweight graph RAG on Rotten Tomatoes movie reviews

40 346

📌 How AI Agents “Talk” to Each Other 🗂 Category: THE VARIABLE 🕒 Date: 2025-06-13 | ⏱️ Read time: 3 min read Minimize chaos and maintain inter-agent harmony in your projects

40 346

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40 346

📌 AI Is Not a Black Box (Relatively Speaking) 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-13 | ⏱️ Read time: 7 min read Compared to the opacity around human intelligence, AI is more transparent in some very tangible…

40 346

📌 What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-13 | ⏱️ Read time: 7 min read An LLM in 2018 would not have trivialized a complex project, although it could have…

40 346

📌 Stop Building AI Platforms 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-13 | ⏱️ Read time: 7 min read When small and medium companies achieve success in building Data and ML platforms, building AI…

40 346

📌 Agents, APIs, and the Next Layer of the Internet 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-16 | ⏱️ Read time: 13 min read Part I: Shipping Containers for Thought Every so often a simple idea rewires everything. The…

40 346

📌 I Won $10,000 in a Machine Learning Competition — Here’s My Complete Strategy 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-06-16 | ⏱️ Read time: 7 min read Complete guide to feature selection, threshold optimization, and neural network architecture for ML competitions

40 346

📌 Build an AI Agent to Explore Your Data Catalog with Natural Language 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-06-16 | ⏱️ Read time: 7 min read Leverage LLMs to query your Databricks Data Catalog

40 346

📌 Regularisation: A Deep Dive into Theory, Implementation, and Practical Insights 🗂 Category: DATA SCIENCE 🕒 Date: 2025-06-16 | ⏱️ Read time: 70 min read A detailed guide on controlling overfitting and increasing the stability of your models.