Computer Science and Programming

Open in Telegram

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 Italy87 Technologies & Applications816...

📈 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 142 737 subscribers, ranking 816 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 142 737 subscribers.

According to the latest data from 14 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -1 292 over the last 30 days and by -44 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 6.29%. Within the first 24 hours after publication, content typically collects 1.82% reactions from the total number of subscribers.
Post reach: On average, each post receives 8 976 views. Within the first day, a publication typically gains 2 595 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.

📝 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 15 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.

142 737

Subscribers

-4424 hours

-2007 days

-1 29230 days

8 976

Post views

~ 2 59524 hours

~ 3 64748 hours

6.29%

Engagement rate

~ 1

Posts per day

Ads index

beta

Posts Archive

142 714

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

142 714

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

142 714

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

142 714

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

142 714

Learning to See Through Obstructions

142 714

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

142 714

AI Literacy for K-12 School Children

142 714

3D Photography using Context-aware Layered Depth Inpainting

142 714

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

142 714

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

142 714

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

142 714

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

142 714

Gary Marcus Robust AI 17 February 2020

142 714

The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence.

142 714

https://vas3k.com/blog/machine_learning/?fbclid=IwAR3e3_Yy7LyEm7-Yqvuttx_zftCn5hL8NXBRSaut0gp7sT8AlxDbj-q3dNQ and find other free-resources: https://www.marktechpost.com/free-resources/?fbclid=IwAR2XJOTWGEdC9aFSRibXWZAZlLpJY9nmRnS_PDfNOgllc9o_mL3OxJaQleY

142 714

Machine Learning for Everyone with great explanation

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Paper: https://arxiv.org/pdf/2003.05534.pdf Github: https://github.com/sniklaus/softmax-splatting Short Summary: https://www.marktechpost.com/2020/03/14/softmax-splatting-for-video-frame-interpolation/

142 714

Softmax Splatting for Video Frame Interpolation (using Pytorch)

142 714

https://www.marktechpost.com/free-ai-ml-deep-learning-video-lectures/?fbclid=IwAR0Yg2egB85ia-ZMxg_hQBghgVJFbc3Wf3s3qmWWlG-1I7QikH-ZDXA0Gn0

142 714

Set of free AI, ML, Deep Learning, Reinforcement Learning, Computer Vision, Statistics video lectures collections(last updated 20th February 2020 with 140 items)