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

Network:Computer Science and Programming Italy88 Technologies & Applications811...

📈 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 140 416 subscribers, ranking 811 in the Technologies & Applications category and 88 in the Italy region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 140 416 subscribers.

According to the latest data from 01 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -772 over the last 30 days and by -64 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 8.15%. Within the first 24 hours after publication, content typically collects 1.97% reactions from the total number of subscribers.
Post reach: On average, each post receives 11 442 views. Within the first day, a publication typically gains 2 771 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 13.
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 02 September, 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.

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140 416

Subscribers

-6424 hours

-2617 days

-77230 days

11 442

Post views

~ 2 77124 hours

~ 3 80448 hours

8.15%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

140 416

It's CVPR time! We will not meet in person next week at CVPR 2020 Seattle: The conference has gone virtual...

140 416

sticker.webp0.16 KB

140 416

Github link of "AI DeOldify Tool": https://github.com/jantic/DeOldify?fbclid=IwAR2-glzM1UYuWHJWuNKi741bm8aeofZdE1-0v9ZN-6Lmlmh4ta63mn5ydZc —————————————————————————— Masked face recognition dataset👇 Wolrd’s most complete Masked Face Recognition Dataset is Free to Download: https://medium.com/the-programming-hub/wolrds-most-complete-masked-face-recognition-dataset-is-for-free-10d780eed512 ——————————————————————————

140 416

You Can Color Your Grandparent's Old Pictures or Videos with AI DeOldify Tool

140 416

Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models Paper: https://arxiv.org/pdf/2005.07310.pdf Related Codes: https://github.com/airsplay/lxmert https://github.com/ChenRocks/UNITER

140 416

Short over view of Artificial Neural Networks with examples Page: https://www.infinitycodex.in/

140 416

Content-based Image retrieval Paper: https://arxiv.org/abs/2005.02154 Github: https://github.com/PyRetri/PyRetri Installation: https://github.com/PyRetri/PyRetri/blob/master/docs/INSTALL.md

140 416

PyRetri: An open source deep learning based unsupervised image retrieval toolbox built on PyTorch🔥

140 416

https://paperswithcode.com/conference/iclr-2020-1/official?fbclid=IwAR0IHbPMDciaoEtbFdVyqrNtkjCOWmL5vdevMdaONJl2-HkR_q1L4U26AtI

140 416

ICLR 2020 (International Conference on Learning Representations) papers and their codes. Papers ranked based on stars

140 416

CVPR 2020 Paper: https://arxiv.org/abs/2004.01180 Project Page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/ObstructionRemoval Github: https://github.com/alex04072000/ObstructionRemoval

140 416

Learning to See Through Obstructions

140 416

MIT Media Lab https://aieducation.mit.edu/resources

140 416

AI Literacy for K-12 School Children

140 416

3D Photography using Context-aware Layered Depth Inpainting

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Paper: https://drive.google.com/file/d/17ki_YAL1k5CaHHP3pIBFWvw-ztF4CCPP/view Github: https://github.com/vt-vl-lab/3d-photo-inpainting Project: https://shihmengli.github.io/3D-Photo-Inpainting/ Notebook: https://colab.research.google.com/drive/1706ToQrkIZshRSJSHvZ1RuCiM__YX3Bz

140 416

Tasks under Unsupervised learning: https://www.infinitycodex.in/ Deep Unsupervised Learning: Lecture: https://youtu.be/JBb5sSC0JoY Slides: https://bit.ly/34dVGE1 Colab: https://bit.ly/2JEzsl1

140 416

Important Tasks under Unsupervised Learning: Clustering Anomaly detection Dimensionality reduction and CS294-158 Deep Unsupervised Learning from Abbeel et al.

140 416

Article link: https://arxiv.org/ftp/arxiv/papers/2002/2002.06177.pdf