uz
Feedback
Computer Science and Programming

Computer Science and Programming

Kanalga Telegram’da o‘tish

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

Ko'proq ko'rsatish

📈 Telegram kanali Computer Science and Programming analitikasi

Computer Science and Programming (@computer_science_and_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 140 416 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 811-o'rinni va Italiya mintaqasida 88-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 140 416 obunachiga ega bo‘ldi.

01 Sentabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -772 ga, so‘nggi 24 soatda esa -64 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 8.15% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.97% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 11 442 marta ko‘riladi; birinchi sutkada odatda 2 771 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 13 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent sellerflash, github, developer, pricing, waybienad kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
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...

Yuqori yangilanish chastotasi (oxirgi ma’lumot 02 Sentabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

Buy Ad
140 416
Obunachilar
-6424 soatlar
-2617 kun
-77230 kun
Postlar arxiv
Introducing PyTorch3D: An open-source library for 3D deep learning. PyTorch3D: Faster, flexible 3D deep learning research
Introducing PyTorch3D: An open-source library for 3D deep learning. PyTorch3D: Faster, flexible 3D deep learning research

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

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/

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

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

Everybody’s Talkin’: Let Me Talk as You Want This paper presents a method to edit a target portrait footage by taking a seque
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.

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

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

⚠ Message was hidden by channel owner

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 fo
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.

⚠ Message was hidden by channel owner

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

2019 is also finishing with great achievements in AI field. Thanks to the extended report from 'artificial intelligence index
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

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