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Computer Science and Programming

Computer Science and Programming

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Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_science

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πŸ“ˆ Analytical overview of Telegram channel Computer Science and Programming

Channel Computer Science and Programming (@computer_science_and_programming) in the English language segment is an active participant. Currently, the community unites 142 711 subscribers, ranking 816 in the Technologies & Applications category and 87 in the Italy 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 142 711 subscribers.

According to the latest data from 15 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -1 289 over the last 30 days and by -46 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.44%. Within the first 24 hours after publication, content typically collects 1.85% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 9 197 views. Within the first day, a publication typically gains 2 646 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 17.
  • Thematic interests: Content is focused on key topics such as sellerflash, github, developer, pricing, waybienad.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œChannel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_sc...”

Thanks to the high frequency of updates (latest data received on 16 June, 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.

142 711
Subscribers
-4624 hours
-2077 days
-1 28930 days
Posts Archive
Gaussian processes for modern machine learning systems
Gaussian processes for modern machine learning systems

GPyTorch Gaussian processes for modern machine learning systems.

Need help getting started with Computer Vision, Deep Learning, and OpenCV? Comprehensive guideline from Adrian Rosebrock (foudner of pyimagesearch) from beginner to advanced level with practical examples:

The current state of AI and Deep Learning: A reply to Yoshua Bengio. Interesting article to know current state and future perspectives of AI and Deep Learning from experts of the field

You are still thinking which Machine Learning framework to learn or use your projects. In 2019, the war for ML frameworks has two remaining main contenders: PyTorch and TensorFlow.

⚠ Message was hidden by channel owner

If you want to start Deep Learning, but you are thinking about how to start then this article will help you. Here is listed completely free and open-sourced courses in your hand

original source: "World economic forum"

"Talk to books" is a search tool that lets you find the most relevant passages from any book. Tool from Google's AI (100,000 scanned books with 600 million sentences) https://books.google.com/talktobooks/

"Hide and Seek" or "Catch Me if You Can!" game from OpenAI. Only this time the computer is playing it
"Hide and Seek" or "Catch Me if You Can!" game from OpenAI. Only this time the computer is playing it

Learn what parts of the image does a deep learning model pay attention to. AttentioNN to describe attention in neural network
Learn what parts of the image does a deep learning model pay attention to. AttentioNN to describe attention in neural networks.