Artificial Intelligence
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🔒 Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM
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Red:📈 Análisis del canal de Telegram Artificial Intelligence
El canal Artificial Intelligence (@artificial_intelligence_com) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 72 399 suscriptores, ocupando la posición 1 724 en la categoría Tecnologías y Aplicaciones y el puesto 4 344 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 72 399 suscriptores.
Según los últimos datos del 31 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 363, y en las últimas 24 horas de -19, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 6.53%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.94% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 4 727 visualizaciones. En el primer día suele acumular 1 407 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 13.
- Intereses temáticos: El contenido se centra en temas clave como learning, linkedin, linux, udemy, 040k|.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“🔒 Welcome Artificial Intelligence Channel
Buy ads: https://telega.io/c/Artificial_Intelligence_COM”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 01 septiembre, 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.
72 399
Suscriptores
-1924 horas
-1267 días
+36330 días
Archivo de publicaciones
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🔗 Most ML roadmaps
If you’re tired of bloated diagrams and endless theory, this one’s for you.This is the 10-step roadmap I wish someone gave me earlier focused on real-world impact, not just flashy model builds. Swipe through to see: ✅ The core skills you actually need ✅ What separates you from junior talent ✅ What most self-taught engineers skip Whether you’re transitioning from data analyst, coming from software dev, or just trying to stop tutorial-hopping...
72 399
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📌 Awesome CursorRules: A repository of Cursor AI recipes.
Awesome CursorRules is a collection of .cursorrules recipe files for fine-tuning the behavior of Cursor AI. The author of the repository has collected dozens of templates that adapt code generation to specific projects: from mobile applications to blockchain solutions.
The main feature of .cursorrules is flexibility. Developers can write rules that will make AI hints more relevant: for example, take into account the team's code style or the architectural features of the project. This not only speeds up the work, but also reduces the risk of errors.
The collection includes almost all areas of development: frontend (Angular, NextJS, Qwik, React, Solid, Svelte, Vue), backend (Deno, Elixir, ES, Go, Java, Lavarel, NodeJS, Python, TypeScript, WordPress), mobile development (React Native, SwiftUI, TypeScript, Android, Flutter) and specific tasks - integration with Kubernetes or optimization for SOLID principles.
For beginners, there are step-by-step instructions: just copy the file into the project or install the extension for VS Code.
Judging by the reviews, Awesome CursorRules has already become a must-have for those who want to get the most out of Cursor AI.
🖥 GitHub
72 399
🔅 PREMIUM CHANNELS
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🔰 The Coding Space
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218k| 🔰 Linkedin Learning Courses
131k| 🔰 Premium Udemy Courses
129k| 🔰 Web Development
-◦-◦--◦-
109k| 🔰 Learn Python
097k| 🔰 JavaScript Courses
080k| 🔰 Machine Learning
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064k| 🔰 DevOps Tutorials
061k| 🔰 Learn React and NextJs
060k| 🔰 Data Analysis and Databases
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053k| 🔰 Linux and DevOps
045k| 🔰 100 Days of Python
044k| 🔰 Best Telegram Channels
-◦-◦--◦-
042k| 🔰 ChatGPT Mastery
042k| 🔰 Business Training
037k| 🔰 Mobile Development
-◦-◦--◦-
037k| 🔰 Zero to Mastery
036k| 🔰 Udemy Learning
033k| 🔰 Codedamn Courses
-◦-◦--◦-
033k| 🔰 Linkedin Learning
032k| 🔰 React 101
030k| 🔰 Crypto Lessons
-◦-◦--◦-
028k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
72 399
Meme of the day: Waymo robotaxi is circling around one point due to a malfunction.
The company has already responded and promised to fix Delamain's crazy chariot.
#meme
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning Foundations: Prototyping with Edge Impulse
72 399
📂 Full description
Explore the world of machine learning on edge devices with this hands-on course. Robert Gallup—a technologist, designer, and maker—guides you through basic machine learning concepts and workflow. Set up the necessary tools and hardware to develop a voice-driven prototype using the Arduino Nano 33 BLE Sense microcontroller. Discover how to use the Edge Impulse platform to acquire data, train a machine learning model, and generate code for your prototype. Upload and modify the code to complete your prototype using the Arduino IDE. Finally, explore practical challenges in deploying ethical machine learning on edge devices. By the end of this course, you'll be equipped to create your own intelligent prototypes, enhancing your technical portfolio and practical problem-solving abilities.
72 399
🔅 Machine Learning Foundations: Prototyping with Edge Impulse
🌐 Author: Robert Gallup
🔰 Level: Beginner
⏰ Duration: 1h 9m
🌀 Discover how to collect data, train models, and deploy code on the Arduino Nano 33 BLE Sense, making intelligent and responsive prototypes.📗 Topics: Arduino IDE, Machine Learning 📤 Join Artificial Intelligence and Machine Learning for more courses
72 399
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
218k| 🔰 Linkedin Learning Courses
130k| 🔰 Premium Udemy Courses
128k| 🔰 Web Development
-◦-◦--◦-
109k| 🔰 Learn Python
096k| 🔰 JavaScript Courses
079k| 🔰 Machine Learning
-◦-◦--◦-
064k| 🔰 DevOps Tutorials
061k| 🔰 Learn React and NextJs
060k| 🔰 Data Analysis and Databases
-◦-◦--◦-
052k| 🔰 Linux and DevOps
045k| 🔰 100 Days of Python
044k| 🔰 Best Telegram Channels
-◦-◦--◦-
042k| 🔰 Business Training
042k| 🔰 ChatGPT Mastery
037k| 🔰 Mobile Development
-◦-◦--◦-
036k| 🔰 Zero to Mastery
035k| 🔰 Udemy Learning
033k| 🔰 Codedamn Courses
-◦-◦--◦-
032k| 🔰 Linkedin Learning
032k| 🔰 React 101
030k| 🔰 Crypto Lessons
-◦-◦--◦-
027k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📱Artificial Intelligence and Machine Learning
📱Machine Learning for Red Team Hackers by Infosec
72 399
📂 Full description
Explore the ins and outs of hacking machine learning with the cybersecurity training experts at Infosec Institute. Deep dive into topics such as hacking a CAPTCHA system, fuzzing a target, evading malware detection, and attacking machine learning systems. Plus, learn about deepfakes and how to perform backdoor attacks on machine learning.
This course was created by Infosec Institute. We are pleased to host this training in our library.
