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

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网络:Computer Science and Programming 意大利87 技术与应用816...

📈 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 142 711 名订阅者，在 技术与应用 类别中位列第 816，并在 意大利 地区排名第 87 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 142 711 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。

142 711

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

142 697

Centre for Computational Statistics and Machine Learning from UCL's Machine Learning Summer School (MLSS'19) video lectures The topics range from optimization and Bayesian inference to deep learning, reinforcement learning, and Gaussian processes. The lectures are of tutorial style, starts from basics, but then quickly picking up the pace so that after 2-4 hours of teaching, they arrive at the state of the art in the subject area.

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https://towardsdatascience.com/everything-you-need-to-know-about-tensorflow-2-0-b0856960c074

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Everything you need to know about TensorFlow 2.0

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More information available at MIT website: http://news.mit.edu/2019/ai-programming-gen-0626 Source code available at: https://probcomp.github.io/Gen/

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MIT Release New AI Programming Language Called ‘GEN’. New AI programming language goes beyond deep learning. General-purpose language works for computer vision, robotics, statistics, and more.

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https://neurips.cc/Conferences/2019/CallForCompetitions?fbclid=IwAR1-Cr4kLXQqgd7wEVmIuPEleC4W7bASaTDfNc8VrjM7q7pWPBA0bvhuVvM

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NeurIPS | 2019 Thirty-third Conference on Neural Information Processing Systems - Accepted Competitions

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YouTube link: https://youtu.be/4jROlXH9Nvc https://docs.google.com/presentation/d/1zyuwCx7knqnP-LJswlDfWSmk5FhFgFmYJGqdEZn8yhc/edit#slide=id.g33c734b530_0_656 Github link: https://github.com/scoutbee/pytorch-nlp-notebooks

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A Deep Dive into NLP with PyTorch. how to implement more advanced architectures and apply it to real world datasets.

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Platform for Machine Learning methods dependencies 3D visualization

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The platform for Machine Learning methods dependencies 3D visualization THE PROJECT IS AVAILABLE ONLINE: HTTPS://WWW.INFORNOPOLITAN.XYZ/BACKRONYM FOR MORE INFORMATION (medium): HTTPS://MEDIUM.COM/@ASADULAEVARIP/HOW-TO-GENERATE-IDEAS-IN-MACHINE-LEARNING-BDB9A7267392

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Amazing!! Deep Learning-based NLP techniques are going to revolutionize the way we write software. Here's Deep TabNine, a GPT-2 model trained on around 2 million files from GitHub. It becomes you lazy, as well as, helps you write code faster