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 40 365 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 40 365 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.

40 365

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

40 373

📌 Introducing Google’s LangExtract tool 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-11 | ⏱️ Read time: 12 min read Do RAG without doing RAG with this powerful new NLP and data extraction library

40 373

📌 Estimating from No Data: Deriving a Continuous Score from Categories 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-11 | ⏱️ Read time: 13 min read A walk-through of and the maths behind using low-capacity networks to acquire fine-grained scoring when…

40 373

📌 Fine-Tune Your Topic Modeling Workflow with BERTopic 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-12 | ⏱️ Read time: 7 min read Learn how to fine-tune BERTopic settings for more focused, reproducible, and interpretable results

40 373

📌 A Refined Training Recipe for Fine-Grained Visual Classification 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-12 | ⏱️ Read time: 17 min read How FGVC aims to recognize images belonging to multiple subordinate categories of a super-category

40 373

📌 Coconut: A Framework for Latent Reasoning in LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-12 | ⏱️ Read time: 12 min read Explaining Coconut (Training Large Language Models to Reason in a Continuous Latent Space) in simple…

40 373

📌 Model Predictive Control Basics 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-12 | ⏱️ Read time: 9 min read A hands-on tutorial with Python and CasADi

40 373

📌 Reducing Time to Value for Data Science Projects: Part 4 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-12 | ⏱️ Read time: 11 min read Embrace your inner software developer

40 373

📌 A Bird’s-Eye View of Linear Algebra: Why Is Matrix Multiplication Like That? 🗂 Category: MATH 🕒 Date: 2025-08-13 | ⏱️ Read time: 21 min read Since the way we manipulate high-dimensional vectors is primarily matrix multiplication, it isn’t a stretch…

40 373

📌 Tips for Setting Expectations in AI Projects 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-08-13 | ⏱️ Read time: 8 min read If you want your AI project to succeed, mastering expectation management comes first. When working…

40 373

📌 Data Mesh Diaries: Realities from Early Adopters 🗂 Category: DATA ENGINEERING 🕒 Date: 2025-08-13 | ⏱️ Read time: 7 min read Early-adopter realities gathered from real data mesh implementations

40 373

📌 How to Use LLMs for Powerful Automatic Evaluations 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-13 | ⏱️ Read time: 7 min read A beginner-friendly introduction to LLM-as-a-Judge

40 373

📌 “My biggest lesson was realizing that domain expertise matters more than algorithmic complexity.“ 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2025-08-14 | ⏱️ Read time: 8 min read Claudia Ng reflects on real-world ML lessons, mentoring newcomers, and her journey from corporate ML…

40 373

📌 What Does “Following Best Practices” Mean in the Age of AI? 🗂 Category: THE VARIABLE 🕒 Date: 2025-08-14 | ⏱️ Read time: 3 min read How data and ML practitioners should navigate a rapidly changing landscape

40 373

📌 LangGraph 101: Let’s Build A Deep Research Agent 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-14 | ⏱️ Read time: 32 min read Learn LangGraph fundamentals from Google’s open-source full-stack implementation

40 373

📌 How to Create Powerful LLM Applications with Context Engineering 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-18 | ⏱️ Read time: 7 min read Improve your LLM by optimizing its context

40 373

📌 How to Correctly Apply Limits on the Result in DAX (and SQL) 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-18 | ⏱️ Read time: 8 min read What if the output of a measure mustn’t be above a specific limit? How can…

40 373

📌 Maximizing AI/ML Model Performance with PyTorch Compilation 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-18 | ⏱️ Read time: 31 min read Since its inception in PyTorch 2.0 in March 2023, the evolution of torch.compile has been one of…

40 373

📌 Extracting Structured Data with LangExtract: A Deep Dive into LLM-Orchestrated Workflows 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-06 | ⏱️ Read time: 10 min read A guide to building modular workflows for structured intelligence

40 373

📌 Modular Arithmetic in Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-18 | ⏱️ Read time: 10 min read Modular arithmetic is a mathematical system where numbers cycle back to the beginning after reaching…

40 373

📌 Can LangExtract Turn Messy Clinical Notes into Structured Data? 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-18 | ⏱️ Read time: 7 min read Turning raw clinical notes into structured entities with LLMs.