Don't get caught by a cheater! Telemetrio finds and tags such channels 👉 If you want to see the tag, subscribe

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 ProgrammingItaly88Technologies & Applications817...

📈 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 138 823 subscribers, ranking 817 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 138 823 subscribers.

According to the latest data from 01 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -923 over the last 30 days and by -43 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 5.49%. Within the first 24 hours after publication, content typically collects 1.72% reactions from the total number of subscribers.
Post reach: On average, each post receives 7 618 views. Within the first day, a publication typically gains 2 394 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 02 November, 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.

Buy Ad

138 823

Subscribers

-4324 hours

-4127 days

-92330 days

7 618

Post views

~ 2 39424 hours

~ 3 43548 hours

5.49%

Engagement rate

No data

Posts per day

Ads index

Posts Archive

138 823

Classification library https://github.com/Tessellate-Imaging/monk_v1 Notebooks - https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/4_image_classification_zoo Detection and Segmentation Library https://github.com/Tessellate-Imaging/ Monk_Object_Detection Notebooks: https://github.com/Tessellate-Imaging/Monk_Object_Detection/tree/master/application_model_zoo

138 823

80+ Jupyter Notebook tutorials on image classification, object detection and image segmentation in various domains 📌 Agriculture and Food 📌 Medical and Healthcare 📌 Satellite 📌 Security and Surveillance 📌 ADAS and Self Driving Cars 📌 Retail and E-Commerce 📌 Wildlife

138 823

Blog: https://towardsdatascience.com/pp-yolo-surpasses-yolov4-object-detection-advances-1efc2692aa62 Github: https://github.com/PaddlePaddle/PaddleDetection

138 823

Baidu publishes PP-YOLO and pushes the state of the art in object detection research.

138 823

Tackled the problem of defining a perturbation set for real-world perturbations which cannot be easily described with a set of equations. Paper: https://arxiv.org/abs/2007.08450 Blog post: https://locuslab.github.io/2020-07-20-perturbation/ Code: https://github.com/locuslab/perturbation_learning

138 823

Learning perturbation sets for robust machine learning

138 823

https://laconicml.com/

138 823

One more great source of Data Science, Deep Learning, Machine Learning, Computer Vision, AI and more... Enjoy with hot topics and projects

138 823

https://github.com/rasbt/deeplearning-models

138 823

Up-to-date and detailed explanation of Deep Learning Models from Sebastian Raschka A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks. (80 Jupyter Notebook notes in total)

138 823

https://arxiv.org/pdf/2003.11755.pdf

138 823

Recently published Comprehensive survey about role of Deep Learning for Scientific discovery (March, 2020). Well structured information given from the authors by providing supplementary materials (Github code links). It worth to spend time to read.

138 823

https://aihub.org/

138 823

One more great website specialized to AI with News, Articles, Opinions, Tutorials, Resources and much more supported by Geeks of AI

138 823

https://laconicml.com/free-artificial-intelligence-courses/?fbclid=IwAR2oQoGYdTqiQ6sOJC7LvJxpaeSVVBLwk6Fs7S-_p2iMDq-BqbrpqBUqUrc

138 823

List some of the free Artificial Intelligence courses that come from Harvard University, MIT University, and Stanford University that anyone can attend, no matter where you live

138 823

But, You can follow what happens there almost in real time: fill below link and receive every day during CVPR the official magazine CVPR Daily (16-17-18 June) - with all the highlights from CVPR, the Computer Vision and Pattern Recognition conference. https://www.rsipvision.com/feel-at-cvpr-as-if-you-were-at-cvpr/ Open Access version of papers are available at: http://openaccess.thecvf.com/CVPR2020.py

138 823

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

138 823

sticker.webp0.16 KB