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

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شبکه:Computer Science and Programming ايطاليا88 فناوری و برنامه‌ها811...

📈 تحلیل کانال تلگرام Computer Science and Programming

کانال Computer Science and Programming (@computer_science_and_programming) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 140 431 مشترک است و جایگاه 811 را در دسته فناوری و برنامه‌ها و رتبه 88 را در منطقه ايطاليا دارد.

📊 شاخص‌های مخاطب و پویایی

از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 140 431 مشترک جذب کرده است.

بر اساس آخرین داده‌ها در تاریخ 01 سپتامبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -772 و در ۲۴ ساعت گذشته برابر -64 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.

وضعیت تأیید: تأیید نشده
نرخ تعامل (ER): میانگین تعامل مخاطب 8.15% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.97% واکنش نسبت به کل مشترکان کسب می‌کند.
دسترسی پست‌ها: هر پست به طور میانگین 11 442 بازدید دریافت می‌کند. در اولین روز معمولاً 2 771 بازدید جمع‌آوری می‌شود.
واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 13 است.
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نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“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...”

به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 02 سپتامبر, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.

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140 431

مشترکین

-6424 ساعت

-2617 روز

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11 442

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~ 2 77124 ساعت

~ 3 80448 ساعت

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140 412

https://ai.facebook.com/blog/-introducing-pytorch3d-an-open-source-library-for-3d-deep-learning/

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Introducing PyTorch3D: An open-source library for 3D deep learning. PyTorch3D: Faster, flexible 3D deep learning research

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https://towardsdatascience.com/end-to-end-machine-learning-from-data-collection-to-deployment-ce74f51ca203 If you want to play with the app and see how it looks like: 💻Demo: https://www.reviews.ai2prod.com/ Code: https://github.com/MarwanDebbiche/post-tuto-deployment

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End to End Machine Learning: From Data Collection to Deployment. - Collect and scrape data with Scrapy / Selenium - Train a deep character CNN for (English) sentiment analysis using PyTorch - Build an interactive web app with Dash to serve the model in real-time - Put everything in Docker Compose - Deploy to AWS on a custom domain name

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More than 200 NLP datasets - this is gold (last update 21.01.202) https://quantumstat.com/dataset/dataset.html and also Google provided dataset search tool for publicly available datasets: https://datasetsearch.research.google.com/

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Paper: https://arxiv.org/pdf/2001.05613.pdf Project page: http://www.ynl.t.u-tokyo.ac.jp/research/vmocap-syn/ Dataset will be available publicly soon

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Synergetic Reconstruction from 2D Pose and 3D Motion for Wide-Space Multi-Person Video Motion Capture in the Wild

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Paper pdf: https://arxiv.org/pdf/2001.05201.pdf Github: https://wywu.github.io/projects/EBT/EBT.html Youtube: https://youtu.be/tNPuAnvijQk

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Everybody’s Talkin’: Let Me Talk as You Want This paper presents a method to edit a target portrait footage by taking a sequence of audio as input to synthesize a photo-realistic video.

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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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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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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