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 Siria228 Tecnologías y Aplicaciones3 381...

📈 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 40 191 suscriptores, ocupando la posición 3 381 en la categoría Tecnologías y Aplicaciones y el puesto 228 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 191 suscriptores.

Según los últimos datos del 01 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 355, 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 2.04%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.12% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 818 visualizaciones. En el primer día suele acumular 851 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
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 02 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.

40 191

Suscriptores

+2124 horas

+857 días

+35530 días

818

Visitas de la publicación

~ 85124 horas

~ 1 13948 horas

2.04%

Tasa de compromiso

~ 3

Mensajes por día

Ads index

beta

Archivo de publicaciones

40 191

📌 Metrics to Evaluate a Classification Machine Learning Model 🗂 Category: 🕒 Date: 2024-07-31 | ⏱️ Read time: 8 min read A study case of credit card fraud

40 191

📌 8 Practical Prompt Engineering Tips for Better LLM Apps 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-01 | ⏱️ Read time: 10 min read How to boost your LLM-native apps with 8 actionable prompt engineering tips for performance, production…

40 191

📌 SQL Optimization, Data Science Portfolios, and Other July Must-Reads 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-01 | ⏱️ Read time: 4 min read The stories that resonated the most with our community in the past month

40 191

📌 Local LLM Fine-Tuning on Mac (M1 16GB) 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-08-01 | ⏱️ Read time: 9 min read Beginner-friendly Python code walkthrough (ft. MLX)

40 191

📌 Introduction to Interpretable Clustering 🗂 Category: 🕒 Date: 2024-08-01 | ⏱️ Read time: 13 min read What is interpretable clustering and why is it important.

40 191

📌 Economics of Generative AI 🗂 Category: BUSINESS 🕒 Date: 2024-08-01 | ⏱️ Read time: 8 min read What’s the business model for generative AI, given what we know today about the technology…

40 191

📌 Building a RAG Pipeline with MongoDB: Vector Search for Personalized Movie Picks 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-08-01 | ⏱️ Read time: 9 min read Learn how to integrate LLMs and MongoDB for precise, context-aware suggestion systems

40 191

📌 How I Built My First RAG Pipeline 🗂 Category: 🕒 Date: 2024-08-02 | ⏱️ Read time: 6 min read A RAG pipeline to answer all of your recruiters’ questions for you!

40 191

📌 The Top 10 Data Lifecycle Problems that Data Engineering Solves 🗂 Category: ANALYTICS 🕒 Date: 2024-08-02 | ⏱️ Read time: 16 min read Clear strategies for addressing key pain points

40 191

📌 3 Surprising Use-cases for Branching in Airflow you’ve not seen before 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-08-02 | ⏱️ Read time: 4 min read Introduction How often is it that you’re writing a Data Pipeline and then you wish…

40 191

📌 Python Code Playground in MkDocs 🗂 Category: PRODUCTIVITY 🕒 Date: 2024-08-02 | ⏱️ Read time: 6 min read Making documentation come to life

40 191

📌 TDS Newsletter: September Must-Reads on ML Career Roadmaps, Python Essentials, AI Agents, and More 🗂 Category: THE VARIABLE 🕒 Date: 2025-10-02 | ⏱️ Read time: 3 min read Don’t miss our most-read and -shared articles of the past month

40 191

Ever wondered how much smarter your workflow could be with AI? Meet Padma AI — your personal Telegram bot that makes work faster, easier, smarter. Try out the AI assistant everyone’s talking about now — and see how much more you can do in a day. Don’t miss your edge — join Padma AI and upgrade your routine! #ad InsideAds

40 191

Missed the latest Kaiju battle? Season 2 of “Kaiju No.8” ⛩️ is almost here—now in Hindi dub! Be first to watch exclusive episodes, insider updates, and surprise drops right here. Don’t wait—join now to catch every epic moment before anyone else. Ready for the ultimate anime experience? Subscribe now! #ad InsideAds

40 191

Missed the last big airdrop? Don’t repeat it. Padma turns grinding into a clear loop: finish daily quests, unlock upgrades and artifacts drops, and convert progress into PAD tokens. Start early this season to grab higher multipliers and leaderboard rewards. Start now! #ad InsideAds

40 191

📌 AI Hallucinations: Can Memory Hold the Answer? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-02 | ⏱️ Read time: 7 min read Exploring How Memory Mechanisms Can Mitigate Hallucinations in Large Language Models

40 191

📌 5 PCA Visualizations You Must Try On Your Next Data Science Project 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-02 | ⏱️ Read time: 8 min read Which features carry the most weight? How do original features contribute to principal components? These…

40 191

📌 Train/Fine-Tune Segment Anything 2 (SAM 2) in 60 Lines of Code 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-08-03 | ⏱️ Read time: 15 min read A step-by-step tutorial for fine-tuning SAM2 for custom segmentation tasks.

40 191

📌 Text Vectorization Demystified: Transforming Language into Data 🗂 Category: 🕒 Date: 2024-08-03 | ⏱️ Read time: 13 min read An intuitive guide to text vectorization

40 191

📌 PySpark Explained: Delta Tables 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-03 | ⏱️ Read time: 15 min read Learn how to use the building blocks of Delta Lakes.