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Artificial Intelligence
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🔒 Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM
Mostrar más📈 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 70 419 suscriptores, ocupando la posición 1 849 en la categoría Tecnologías y Aplicaciones y el puesto 4 785 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 70 419 suscriptores.
Según los últimos datos del 13 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 1 217, y en las últimas 24 horas de 69, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.35%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.09% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 5 179 visualizaciones. En el primer día suele acumular 1 474 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 10.
- 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 14 junio, 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.
70 419
Suscriptores
+6924 horas
+2577 días
+1 21730 días
Archivo de publicaciones
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217k| 🔰 Linkedin Learning Courses
126k| 🔰 Premium Udemy Courses
125k| 🔰 Web Development
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103k| 🔰 Learn Python
094k| 🔰 JavaScript Courses
074k| 🔰 Machine Learning
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065k| 🔰 DevOps Tutorials
058k| 🔰 Learn React and NextJs
054k| 🔰 Data Analysis and Databases
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049k| 🔰 Linux and DevOps
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039k| 🔰 Business Training
038k| 🔰 ChatGPT Mastery
035k| 🔰 Mobile Development
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034k| 🔰 Zero to Mastery
032k| 🔰 Udemy Learning
031k| 🔰 Codedamn Courses
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031k| 🔰 Linkedin Learning
030k| 🔰 React 101
029k| 🔰 Crypto Lessons
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025k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
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🔗 30 Useful AI Apps That Can Help You in 2025
AI apps are taking over the world. There’s an AI app for every conceivable use case. Here are some AI apps for different categories:1 - General Purpose: Perplexity, Anthropic Claude, Grok, ChatGPT, and Gemini 2 - Writing Code: Cursor, Replit, Windsurf AI, Github Copilot, and Tabnine 3 - Productivity: Adobe (PDF Chat), Gemini for Gmail, Gamma (AI slide deck), WisprFlow (AI voice dictation), and Granola (AI notetaker) 4 - Audience Building: Delphi (AI text, voice), HeyGen (video translation), Persona (AI agent builder), Captions (AI video editing), and OpusClips (Video repurposing) 5 - Creativity: ElevenLabs (realistic AI voices), Midjourney, Suno AI (music generation), Krea (enhance images), and Photoroom (AI image editing) 6 - Learning and Growth: Particle News App, Rosebud (AI journal app), NotebookLM, GoodInside (parenting co-pilot), and Ash (AI counselor).
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🔰 The Coding Space
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217k| 🔰 Linkedin Learning Courses
125k| 🔰 Premium Udemy Courses
125k| 🔰 Web Development
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103k| 🔰 Learn Python
094k| 🔰 JavaScript Courses
074k| 🔰 Machine Learning
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065k| 🔰 DevOps Tutorials
058k| 🔰 Learn React and NextJs
054k| 🔰 Data Analysis and Databases
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049k| 🔰 Linux and DevOps
043k| 🔰 Best Telegram Channels
042k| 🔰 100 Days of Python
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039k| 🔰 Business Training
038k| 🔰 ChatGPT Mastery
035k| 🔰 Mobile Development
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034k| 🔰 Zero to Mastery
032k| 🔰 Udemy Learning
031k| 🔰 Codedamn Courses
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030k| 🔰 Linkedin Learning
030k| 🔰 React 101
029k| 🔰 Crypto Lessons
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025k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
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🔰 Add Your Channel
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🔰 2hrs on top & 8hrs in channel!
70 430
🔅 PREMIUM CHANNELS
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🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning Courses
125k| 🔰 Premium Udemy Courses
124k| 🔰 Web Development
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102k| 🔰 Learn Python
093k| 🔰 JavaScript Courses
074k| 🔰 Machine Learning
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065k| 🔰 DevOps Tutorials
058k| 🔰 Learn React and NextJs
053k| 🔰 Data Analysis and Databases
-◦-◦--◦-
048k| 🔰 Linux and DevOps
043k| 🔰 Best Telegram Channels
042k| 🔰 100 Days of Python
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039k| 🔰 Business Training
038k| 🔰 ChatGPT Mastery
035k| 🔰 Mobile Development
-◦-◦--◦-
033k| 🔰 Zero to Mastery
032k| 🔰 Udemy Learning
031k| 🔰 Codedamn Courses
-◦-◦--◦-
030k| 🔰 Linkedin Learning
030k| 🔰 React 101
029k| 🔰 Crypto Lessons
-◦-◦--◦-
025k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
70 430
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning Courses
125k| 🔰 Premium Udemy Courses
124k| 🔰 Web Development
-◦-◦--◦-
102k| 🔰 Learn Python
093k| 🔰 JavaScript Courses
073k| 🔰 Machine Learning
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065k| 🔰 DevOps Tutorials
058k| 🔰 Learn React and NextJs
053k| 🔰 Data Analysis and Databases
-◦-◦--◦-
048k| 🔰 Linux and DevOps
043k| 🔰 Best Telegram Channels
042k| 🔰 100 Days of Python
-◦-◦--◦-
039k| 🔰 Business Training
037k| 🔰 ChatGPT Mastery
035k| 🔰 Mobile Development
-◦-◦--◦-
033k| 🔰 Zero to Mastery
031k| 🔰 Udemy Learning
031k| 🔰 Codedamn Courses
-◦-◦--◦-
030k| 🔰 Linkedin Learning
030k| 🔰 React 101
029k| 🔰 Crypto Lessons
-◦-◦--◦-
024k| 🔰 Coding Interview
022k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
70 430
📱Artificial Intelligence and Machine Learning
📱Artificial Intelligence Foundations: Machine Learning
70 430
📂 Full description
Machine learning is the most exciting branch of artificial intelligence. It allows systems to learn from data by identifying patterns and making decisions with little to no human intervention. In this course, you'll navigate the machine learning lifecycle by getting hands-on practice training your first machine learning model. Join instructor Kesha Williams as she explores widely adopted machine learning methods: supervised, unsupervised, and reinforcement. There's a focus on sourcing and preparing data and selecting the best learning algorithm for your project. After training a model, learn to evaluate model performance using standard metrics. Finally, Kesha shows you how to streamline the process by building a machine learning pipeline. If youre looking to understand the machine learning lifecycle and the steps required to build systems, check out this course.
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🔅 Artificial Intelligence Foundations: Machine Learning
🌐 Author: Kesha Williams
🔰 Level: Beginner
⏰ Duration: 1h 50m
🌀 Learn about the machine learning lifecycle and the steps required to build systems in this hands-on course.📗 Topics: Machine Learning, Artificial Intelligence 📤 Join Artificial Intelligence and Machine Learning for more courses
70 430
🔅 PREMIUM CHANNELS
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🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning Courses
124k| 🔰 Premium Udemy Courses
123k| 🔰 Web Development
-◦-◦--◦-
101k| 🔰 Learn Python
093k| 🔰 JavaScript Courses
073k| 🔰 Machine Learning
-◦-◦--◦-
065k| 🔰 DevOps Tutorials
057k| 🔰 Learn React and NextJs
052k| 🔰 Data Analysis and Databases
-◦-◦--◦-
048k| 🔰 Linux and DevOps
043k| 🔰 Best Telegram Channels
042k| 🔰 100 Days of Python
-◦-◦--◦-
038k| 🔰 Business Training
037k| 🔰 ChatGPT Mastery
034k| 🔰 Mobile Development
-◦-◦--◦-
033k| 🔰 Zero to Mastery
031k| 🔰 Udemy Learning
031k| 🔰 Codedamn Courses
-◦-◦--◦-
030k| 🔰 Linkedin Learning
029k| 🔰 React 101
028k| 🔰 Crypto Lessons
-◦-◦--◦-
024k| 🔰 Coding Interview
022k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
70 430
8. Set up the user interface and trigger the main function.
• Provides an input field for the user's question
• Triggers the main function when the user clicks "Get Answer"
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7. Define the main function to run all LLMs and aggregate results.
• Runs all reference models asynchronously
• Displays individual responses in expandable sections
• Aggregates responses using the aggregator model
• Streams the aggregated response.
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6. Implement the LLM call function.
• Asynchronously calls the LLM with the user's prompt
• Returns the model name and its response
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5. Define the models and aggregator system prompt.
• Specifies the LLMs to be used for generating responses
• Defines the aggregator model and its system prompt
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4. Initialize Together AI clients.
• Sets up Together API key as an environment variable
• Initializes both synchronous and asynchronous Together clients
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3. Set up the Streamlit app and API key input.
• Creates a title for the app
• Adds a secure input field for the Together API key
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2. Import necessary libraries
• Streamlit for the web interface
• asyncio for asynchronous operations
• Together AI for LLM interactions
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1. Install the necessary Python Libraries
Run the following commands from your terminal to install the required libraries:
