Computer Science and Programming

前往频道在 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

显示更多

网络:Computer Science and Programming 意大利86 技术与应用813...

📈 Telegram 频道 Computer Science and Programming 的分析概览

频道 Computer Science and Programming (@computer_science_and_programming) 英语语言赛道中的是活跃参与者。目前社区聚集了 142 667 名订阅者，在 技术与应用 类别中位列第 813，并在 意大利 地区排名第 86 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 142 667 名订阅者。

根据 15 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -1 289，过去 24 小时变化为 -46，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 6.44%。内容发布后 24 小时内通常能获得 1.85% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 9 197 次浏览，首日通常累积 2 646 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 17。
主题关注点： 内容集中在 sellerflash, github, developer, pricing, waybienad 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“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...”

凭借高频更新（最新数据采集于 16 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。

142 667

订阅者

-4624 小时

-2077 天

-1 28930 天

9 197

帖子浏览量

~ 2 64624 小时

~ 3 57748 小时

6.44%

参与率

~ 1

每日帖子数

Ads index

beta

帖子存档

142 649

deeplearningforcomputervision.pdf51.85 MB

142 649

Rajalingappaa Shanmugamani "Deep Learning for Computer Vision" (2018). Highly recommend. #DeepLearning , #Keras , #Tensorflow

142 649

https://www.datasciencecentral.com/profiles/blogs/neural-networks-for-machine-learning

142 649

30 Free Courses: Neural Networks, Machine Learning, Algorithms, AI

142 649

Just another advance of #GAN algorithm family. Pay attention to this video with #BigGAN

142 649

Practical Machine Learning with Python (2018).pdf19.39 MB

142 649

Book: "Practical Machine Learning with Python" published in 2018 with good content for practical learning by D. Sarkar, R.Bali, T.Sharma

142 649

https://www.facebook.com/nipsfoundation/?__tn__=%2Cdk%2CP-R&eid=ARCq4f7db0t5fpd0RMQa8wqmTg8xQMN1asHzOVhn19zQ8VWpH3vi-4YL-aLHC6DcpHAD2CQj6Q4Sa86N

142 649

As you know, one of the important event in AI world #NeurIPS2018 (Neural Information Processing Systems) is going in Montreal. Here is you can learn from up-to-date tutorials from scholar of AI world:

142 649

https://gandissect.csail.mit.edu/

142 649

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.

142 649

https://skymind.ai/wiki/

142 649

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

142 649

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

142 649

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

142 649

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

142 649

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.

142 649

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