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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
Thrilled to be teaching a new course on Deep Unsupervised Learning with Peterxichen (ImprovedGAN, InfoGAN, PixelCNN++, VLAE, PixelSNAIL, Flow++), Hojonathanho (Flow++, GAIL), Aravind(Flow++): * Lectures * Homeworks

Google IO 2019 keynote. Learn about the latest product and platform innovations at Google in a Keynote Several improvements are introduced this year in AI + Software + Hardware integration. πŸ‘‡

Great Tensorflow tutorial Series from Hvass Laboratories, which one of the most dominating Deep Learning Framework with practical examples

SafeML ICLR 2019 Workshop accepted papers list. Read and explore new horizons of Machine Learning

I highly recommend the Cornell University's "Machine Learning for Intelligent Systems (CS4780/ CS5780)" course taught by Associate Professor Kilian Q. Weinberger.

"One Model to Rule Them All" Christoph Molnar. Some experienced toughts how to work effectively with your Machine Learning model(project)

Deep Learning lecture

Deep Learning lecture The full deck of (600+) slides, by Professor Gilles Louppe. PDF file available here:

Faster in Python with Line-of-Code Completions. Machine-learning applied to programming in Python.

Imrove your skills by Learning and Practicing Python, Machine Learning, Deep Learning (beginner, intermediate, advanced topic
Imrove your skills by Learning and Practicing Python, Machine Learning, Deep Learning (beginner, intermediate, advanced topic). Complete tutorial categorized series from data-flair

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