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 Italy87 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 140 395 subscribers, ranking 811 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 140 395 subscribers.

According to the latest data from 02 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -753 over the last 30 days and by -1 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 8.00%. Within the first 24 hours after publication, content typically collects 2.00% reactions from the total number of subscribers.
Post reach: On average, each post receives 11 237 views. Within the first day, a publication typically gains 2 812 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 14.
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 03 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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140 395

Subscribers

-124 hours

-2397 days

-75330 days

11 237

Post views

~ 2 81224 hours

~ 3 85648 hours

8.00%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

140 398

Intelligent painting with GAN by directly activating and deactivating sets of neurons in a deep network trained to generate images. Code and Data, Paper, Video and Interactive demo is available.

140 398

https://skymind.ai/wiki/

140 398

Artificial Intelligence wiki from skimind ai team. Everything about AI, DL and ML. Great recourse

140 398

http://en.diveintodeeplearning.org/index.html

140 398

"Dive into Deep Learning" An interactive deep learning book for students, engineers, and researchers.

140 398

https://github.com/arXivTimes/arXivTimes/tree/master/datasets

140 398

Datasets list by categories and description, which we can use for machine learning practices. Article originally written in Japanese language, but I hope in your browser "translate page" extension is turned on and you have no problem. Enjoy with playing with datasets in your research.

140 398

https://github.com/MikeTheWatchGuy/PySimpleGUI/tree/master/YoloObjectDetection?fbclid=IwAR0jx0ehVlbWBhFrlxyd60sHqR2N0rt4CqneMh72zd5JbvXb7RxVbrHj1Lc

140 398

From command line into a GUI. YOLO demonstration running inside of a PySimpleGUI. Instruction is clearly given in project's github repository

140 398

https://github.com/PacktPublishing/Advanced-Deep-Learning-with-Keras

140 398

"Advanced Deep Learning with Keras" by Rowel Atienza (Published october, 2018). I am providing this book's github repo for practicing directly with codes. You can learn about key points of Keras and series of GAN. I hope you enjoy

140 398

https://github.com/rasbt/python-machine-learning-book-2nd-edition?fbclid=IwAR09MQmadI0LMdFBiXs10g9dNkSo1Jtq0dpw6tJU-I2rqR7UDNsfyQC6KEQ

140 398

The "Python machine learning book 2nd edition" book code repository. With practical examples and provided Notebook file for convinience

140 398

https://medium.com/@jonathan_hui/gan-gan-series-2d279f906e7b

140 398

All about GANs: Application area, performance, improvements, difficulties, issues, optimization, ...

140 398

https://github.com/hindupuravinash/the-gan-zoo

140 398

Since is introduced by Ian Goodfellow (in 2014), GANs ( Generative Adversarial Networks) gained high attention among AI world and in challenging area of research, as well as, developed many frameworks and cool applications based GANs. Below We share link about list of fraweworks, which created and applied for certain research are based on GANs.

140 398

https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/

140 398

Jupyter Notebook is becoming most dominant IDE for many programming languages (especially, Python). In this link provided useful tips, tricks, and shortcuts about Jupyter Notebook