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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 140 431 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 140 431 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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140 431
Subscribers
-6424 hours
-2617 days
-77230 days
Posts Archive
Catch up with all the exciting tutorials of International Conference of Machine Learning (ICML'19) here. Indexed with Table o
Catch up with all the exciting tutorials of International Conference of Machine Learning (ICML'19) here. Indexed with Table of Content and powered by VideoKen deep video search

All 1,294 papers at #CVPR2019 in one link. Enjoy woth up-to-date research papers and hot topics of #ArtificialIntelligence #DeepLearning #MachineLearning

A Gentle Introduction to Text Summarization in Machine Learning from FLOYDHUB

https://github.com/lutzroeder/netron Supports: Mac OS, Windows, Linux, Browser version, Python Server

Netron is a viewer for neural network, deep learning and machine learning models.

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more

Detailed explanation at paper: 👇 https://arxiv.org/pdf/1905.10498.pdf and it's implementation and some results by using pytorch: 👇 https://github.com/facebookresearch/qmnist

MNIST reborn, restored and expanded. Now with an extra 50,000 training samples. If you used the original MNIST test set more than a few times, chances are your models overfit the test set. Time to test them on those extra samples. Now you will use #QMNIST instead of #MNIST

website, which will provide you all up-to-date and necessary information on Artificial Intelligence, Machine Learning, Deep Learning and some brain activities. You will also find TED Talks, Lectures and academic writings on these issues.

Speech2Face: Learning the Face behind a Voice #CVPR2019
Speech2Face: Learning the Face behind a Voice #CVPR2019

Samsung AI's latest work on #GAN to animate realistic head model sequences is setting the internet on fire

Supervisely: end-to-end web-platform for Deep Learning and Computer Vision