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

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Paper link: https://arxiv.org/pdf/1904.02689.pdf Github repo: https://github.com/dbolya/yolact

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YOLACT (You Only Look At CoefficienTs) - Real-time Instance Segmentation Results are impressive, above 30 FPS on COCO test-dev

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However, great resource from data-flair team and there are waiting you 240+ Python Tutorials from scratch (under advanced, intermediate, beginner categories): https://data-flair.training/blogs/python-tutorials-home/ and you'll also follow their telegram channels for fresh news from original source: https://t.me/dataflair

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⚠ Message was hidden by channel owner

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These Projects will make you the Super Hero of Python: https://medium.com/dataflair/these-projects-will-make-you-the-superhero-of-python-city-14101e62393b

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Happy new year. I would like to share channel's progress for 2019 and we have +29 874 new members for this year. Thank you for all members of channel.

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⚠ Message was hidden by channel owner

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Due to your interest and some specific points, you will read about in more detail from the report: https://hai.stanford.edu/sites/g/files/sbiybj10986/f/ai_index_2019_report.pdf?fbclid=IwAR228NxD7QCdksNYkSPZ2vcpm5Jzk5zCGx9v0NpsAkQVOspv85MvG3LK3wE

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2019 is also finishing with great achievements in AI field. Thanks to the extended report from 'artificial intelligence index' which I highlighted more specific ones (Of cource is just my choise only): 👉 AI Research went crazy. Between 1998 and 2018, there’s been a 300% increase in the publication of peer-reviewed papers on AI. 👉 Attendance at conferences went crazy too, for eg. NeurIPS, got some 13,500 attendees this year, up 800% from 2012. 👉 Education too bumped up, a lot of folks took up MSc / PhD with something in Machine Learning 👉 USA still leads in AI, no matter what other countries say 👉 AI algorithms are becoming cheaper and mainstream 👉 self driving vehicles market is coming of age and raking in a lot of investments

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Here is the pre-reading material is mentioned from organizers: http://montreal.ai/aidebate.pdf And you can also submit your questions by following link: https://montrealartificialintelligence.com/aidebate/?fbclid=IwAR0apri8P3UENmgGhRxeg5k022wh25ynFj7fnJ0OOEd7Kw_vh_6XRfkZA-s Live streaming: https://www.eventbrite.ca/e/debate-yoshua-bengio-gary-marcus-live-streaming-tickets-81620778947?fbclid=IwAR2MG35fVKQvxSXQc4DYXn-q9bVEwmfrqfT98m9IuF1gCgEHGRCx0k0ftmc

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I think, every AI lovers are waiting for AI debate: Yoshua Bengio and Gary Marcus, which a decade that has revived the field of AI

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https://github.com/BMW-InnovationLab?fbclid=IwAR34Mob2EPacL61j9JUElk5Ewv2COlxpDKxE3FdTJqpWMx31KfdA0iUtwf4

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BMW shares AI algorithms used in production, available on GitHub

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https://medium.com/artificial-intelligence-solutions/so-is-your-algorithm-not-working-aa8e4ebd2066?

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Things you need to consider about your algorithm is working or not

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https://www.marktechpost.com/free-resources/?fbclid=IwAR3gRM5OyBnNlYmQLZqQHZTUsh3tCI0bshZXvgxbV90Na5-YLSuHLe4sPOE

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Free AI Resources Find The Most Updated and Free Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Mathematics, Python Programming Resources. (Last Update: December 4, 2019)

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RoboNet Project page: https://www.robonet.wiki/

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Github: https://github.com/SudeepDasari/RoboNet Paper link: https://arxiv.org/abs/1910.11215 Blog: https://blog.ml.cmu.edu/2019/11/26/robonet/?fbclid=IwAR3PtmaSmMPcYuXrJfhaRmykgiMsRHshbJ7pWqBRO-2VcH2IsCSBdvGtkt0

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RoboNet: A Dataset for Large-Scale Multi-Robot Learning (15 million video frames, 7 Robot platform).