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

📌 Mechanistic View of Transformers: Patterns, Messages, Residual Stream… and LSTMs 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-08-05 | ⏱️ Read time: 7 min read What happens when you stop concatenating and start decomposing: a new way to think about…

40 373

📌 Exploratory Data Analysis: Gamma Spectroscopy in Python (Part 3) 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-05 | ⏱️ Read time: 17 min read Let’s observe the matter on the atomic level

40 373

📌 Stellar Flare Detection and Prediction Using Clustering and Machine Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-05 | ⏱️ Read time: 11 min read Combining unsupervised clustering with supervised learning to detect and predict stellar flares

40 373

📌 How a Research Lab Made Entirely of LLM Agents Developed Molecules That Can Block a Virus 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-08-05 | ⏱️ Read time: 10 min read Welcome to the 21st century by the hand of large language models and reasoning AI…

40 373

📌 Things I Wish I Had Known Before Starting ML 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-05 | ⏱️ Read time: 6 min read Part 2: Guardrails, research code, reading

40 373

📌 Context Engineering — A Comprehensive Hands-On Tutorial with DSPy 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-05 | ⏱️ Read time: 18 min read Let’s dissect the art and science of context engineering, one module at a time!

40 373

📌 InfiniBand vs RoCEv2: Choosing the Right Network for Large-Scale AI 🗂 Category: LARGE DATA MODELS 🕒 Date: 2025-08-06 | ⏱️ Read time: 8 min read Learn how InfiniBand and RoCEv2 enable high-speed GPU communication

40 373

📌 The Machine, the Expert, and the Common Folks 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-06 | ⏱️ Read time: 15 min read A look at noise, consistency and broken legs

40 373

📌 How I Won the “Mostly AI” Synthetic Data Challenge 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-08-06 | ⏱️ Read time: 8 min read A deep dive into how post-processing can supercharge synthetic data generation

40 373

📌 The MCP Security Survival Guide: Best Practices, Pitfalls, and Real-World Lessons 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-08-06 | ⏱️ Read time: 30 min read Unless you’re someone who lives and breathes cybersecurity, chances are you didn’t think much about…

40 373

📌 The Channel-Wise Attention | Squeeze and Excitation 🗂 Category: DEEP LEARNING 🕒 Date: 2025-08-07 | ⏱️ Read time: 22 min read Applying the Squeeze and Excitation module on ResNeXt using PyTorch

40 373

📌 Finding Golden Examples: A Smarter Approach to In-Context Learning 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-08-07 | ⏱️ Read time: 7 min read From random example selection to systematic AuPair generation — how to make your LLM prompts actually…

40 373

📌 Agentic AI: On Evaluations 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-07 | ⏱️ Read time: 16 min read Metrics to track for RAG and agents, plus the frameworks that help

40 373

📌 Hands-On with Agents SDK: Safeguarding Input and Output with Guardrails 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-06 | ⏱️ Read time: 18 min read A practical exploration of how guardrails safeguard multi-agent systems in Python using OpenAI Agents SDK,…

40 373

📌 Time Series Forecasting Made Simple (Part 3.2): A Deep Dive into LOESS-Based Smoothing 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-07 | ⏱️ Read time: 6 min read Explore how STL uses LOESS smoothing to extract trend and seasonal components.

40 373

📌 Demystifying Cosine Similarity 🗂 Category: DATA SCIENCE 🕒 Date: 2025-08-08 | ⏱️ Read time: 8 min read Mathematical intuition and practical considerations for NLP scenarios

40 373

📌 Generating Structured Outputs from LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-08-08 | ⏱️ Read time: 13 min read An overview of popular techniques to confine LLMs’ output to a predefined schema

40 373

📌 How to Write Insightful Technical Articles 🗂 Category: WRITING 🕒 Date: 2025-08-08 | ⏱️ Read time: 9 min read Learn how to write informative technical articles

40 373

📌 LangGraph + SciPy: Building an AI That Reads Documentation and Makes Decisions 🗂 Category: AGENTIC AI 🕒 Date: 2025-08-11 | ⏱️ Read time: 11 min read Stop guessing your statistical test. Let this AI do it for you.

40 373

📌 From Genes to Neural Networks: Understanding and Building NEAT (Neuro-Evolution of Augmenting Topologies) from Scratch 🗂 Category: DEEP LEARNING 🕒 Date: 2025-08-11 | ⏱️ Read time: 19 min read Practical Neuroevolution: Reproducing NEAT’s Innovations and Code Walkthrough