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Artificial Intelligence

Artificial Intelligence

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πŸ“ˆ Analytical overview of Telegram channel Artificial Intelligence

Channel Artificial Intelligence (@artificial_intelligence_com) in the English language segment is an active participant. Currently, the community unites 71 596 subscribers, ranking 1 800 in the Technologies & Applications category and 4 426 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 71 596 subscribers.

According to the latest data from 27 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -384 over the last 30 days and by -23 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.09%. Within the first 24 hours after publication, content typically collects 1.59% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 4 365 views. Within the first day, a publication typically gains 1 141 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 7.
  • Thematic interests: Content is focused on key topics such as learning, linkedin, linux, udemy, 040k|.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œπŸ”’ Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM”

Thanks to the high frequency of updates (latest data received on 28 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

71 596
Subscribers
-2324 hours
-2037 days
-38430 days
Posts Archive
πŸ“¦ Exercise Files

πŸ“±Artificial Intelligence and Machine Learning πŸ“±Machine Learning Foundations: Statistics

πŸ”… Machine Learning Foundations: Statistics πŸ“ Learn how statistics can help you troubleshoot issues, optimize performance, a
πŸ”… Machine Learning Foundations: Statistics πŸ“ Learn how statistics can help you troubleshoot issues, optimize performance, and innovate, creating new machine learning models that are more efficient. 🌐 Author: Terezija Semenski πŸ”° Level: Beginner ⏰ Duration: 1h 20m πŸ“‹ Topics: Statistical Analysis, Machine Learning πŸ”— Join Artificial Intelligence and Machine Learning for more courses

SOCKS. MARKET Updates Our Official Channel for platform updates, infrastructure changes, and service announcements related to
SOCKS. MARKET Updates Our Official Channel for platform updates, infrastructure changes, and service announcements related to residential and mobile proxy solutions. Updates only. #ad

🧠 Roadmap for building scalable AI Agents!
🧠 Roadmap for building scalable AI Agents!

⭐️ Top 27 AI Tools
+9
⭐️ Top 27 AI Tools

πŸ“¦ Exercise Files

πŸ“±Artificial Intelligence and Machine Learning πŸ“±Building a Recommendation System with Python Machine Learning and AI

πŸ”… Building a Recommendation System with Python Machine Learning and AI πŸ“ Discover how to use Python to build programs that
πŸ”… Building a Recommendation System with Python Machine Learning and AI πŸ“ Discover how to use Python to build programs that can make recommendations. This hands-on course explores different types of recommendation systems, and shows how to build each one. 🌐 Author: Lillian Pierson, P.E. πŸ”° Level: Intermediate ⏰ Duration: 1h 39m πŸ“‹ Topics: Machine Learning, Recommender Systems πŸ”— Join Artificial Intelligence and Machine Learning for more courses

🧠 Top AI Algorithms And Their Use Cases
🧠 Top AI Algorithms And Their Use Cases

🧠 Machine Learning Algorithms every data scientist must know
🧠 Machine Learning Algorithms every data scientist must know

🧠 AI/ML software stack The AI/ML software stack consists of layered tools that support the entire machine learning lifecycle
🧠 AI/ML software stack The AI/ML software stack consists of layered tools that support the entire machine learning lifecycle, including data management, distributed computing, model development, orchestration, deployment, and monitoring πŸ˜ŽπŸ‘†

πŸ“¦ Exercise Files

πŸ“±Artificial Intelligence and Machine Learning πŸ“±Advanced QGIS Analysis with AI and Machine Learning

πŸ”… Advanced QGIS Analysis with AI and Machine Learning πŸ“ Explore the advanced tools that GIS has to offer and learn how to u
πŸ”… Advanced QGIS Analysis with AI and Machine Learning πŸ“ Explore the advanced tools that GIS has to offer and learn how to use new tools, such as AI and machine learning. 🌐 Author: Gordon Luckett πŸ”° Level: Advanced ⏰ Duration: 2h 22m πŸ“‹ Topics: Machine Learning, Quantum GIS, Geological Mapping πŸ”— Join Artificial Intelligence and Machine Learning for more courses

🀝 7 Most Important Regression Techniques in Data Science
🀝 7 Most Important Regression Techniques in Data Science

πŸ”† Mathematics required for Machine Learning
+3
πŸ”† Mathematics required for Machine Learning

πŸ”† Mathematics required for Machine Learning
+3
πŸ”† Mathematics required for Machine Learning

πŸ”— Different Types of Neural Network
πŸ”— Different Types of Neural Network

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