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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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📈 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 142 510 subscribers, ranking 814 in the Technologies & Applications category and 87 in the Italy region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 142 510 subscribers.

According to the latest data from 18 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -1 227 over the last 30 days and by -56 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 5.75%. Within the first 24 hours after publication, content typically collects 1.99% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 8 193 views. Within the first day, a publication typically gains 2 838 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 15.
  • Thematic interests: Content is focused on key topics such as sellerflash, github, developer, pricing, waybienad.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
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_sc...

Thanks to the high frequency of updates (latest data received on 19 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.

142 510
Subscribers
-5624 hours
-3197 days
-1 22730 days
Posts Archive
Neural Style Transfer: Creating Art with Deep Learning using tf.keras and eager execution

MultiTracker : Multiple Object Tracking using OpenCV (C++/Python)

Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data

Cutting-Edge Face Recognition is Complicated. These Spreadsheets Make it Easier.

Socket Programming in Python (Guide)

Computer Vision News (1).pdf4.03 MB

Computer vision news fron RSIP Vision. August 2018

Python for Secret Agents (en).pdf1.41 MB

Python for Secret Agents – Steven F. Lott (en) 2014 Analyzing, coding, decoding information in Python

Computer Vision, the OpenCV library has 8 (yes, eight!) different algorithms used for robust Object Tracking. After applying Object Detection (typically via YOLO, Faster R-CNN, SSD, etc.), you can then utilize an Object Tracker to uniquely label and track an object in a video stream.

The Algorithms - Python All algorithms implemented in Python (for education)