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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Computer Science and Programming (@computer_science_and_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 142 737 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 816-o'rinni va Italiya mintaqasida 87-o'rinni egallagan.

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невідомо sanasidan buyon loyiha tez o‘sib, 142 737 obunachiga ega bo‘ldi.

14 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -1 292 ga, so‘nggi 24 soatda esa -44 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 6.29% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.82% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 8 976 marta ko‘riladi; birinchi sutkada odatda 2 595 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 17 ta reaksiya keladi.
Tematik yo‘nalishlar: Kontent sellerflash, github, developer, pricing, waybienad kabi asosiy mavzularga jamlangan.

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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 15 Iyun, 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.

142 737

Obunachilar

-4424 soatlar

-2007 kunlar

-1 29230 kunlar

8 976

Post ko'rishlar

~ 2 59524 soatlar

~ 3 64748 soatlar

6.29%

Muloqot nisbati

~ 1

Kuniga postlar

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Postlar arxiv

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Learning perturbation sets for robust machine learning

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https://laconicml.com/

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One more great source of Data Science, Deep Learning, Machine Learning, Computer Vision, AI and more... Enjoy with hot topics and projects

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https://github.com/rasbt/deeplearning-models

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Up-to-date and detailed explanation of Deep Learning Models from Sebastian Raschka A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks. (80 Jupyter Notebook notes in total)

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https://arxiv.org/pdf/2003.11755.pdf

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Recently published Comprehensive survey about role of Deep Learning for Scientific discovery (March, 2020). Well structured information given from the authors by providing supplementary materials (Github code links). It worth to spend time to read.

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https://aihub.org/

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One more great website specialized to AI with News, Articles, Opinions, Tutorials, Resources and much more supported by Geeks of AI

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https://laconicml.com/free-artificial-intelligence-courses/?fbclid=IwAR2oQoGYdTqiQ6sOJC7LvJxpaeSVVBLwk6Fs7S-_p2iMDq-BqbrpqBUqUrc

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List some of the free Artificial Intelligence courses that come from Harvard University, MIT University, and Stanford University that anyone can attend, no matter where you live

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But, You can follow what happens there almost in real time: fill below link and receive every day during CVPR the official magazine CVPR Daily (16-17-18 June) - with all the highlights from CVPR, the Computer Vision and Pattern Recognition conference. https://www.rsipvision.com/feel-at-cvpr-as-if-you-were-at-cvpr/ Open Access version of papers are available at: http://openaccess.thecvf.com/CVPR2020.py

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It's CVPR time! We will not meet in person next week at CVPR 2020 Seattle: The conference has gone virtual...

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Github link of "AI DeOldify Tool": https://github.com/jantic/DeOldify?fbclid=IwAR2-glzM1UYuWHJWuNKi741bm8aeofZdE1-0v9ZN-6Lmlmh4ta63mn5ydZc —————————————————————————— Masked face recognition dataset👇 Wolrd’s most complete Masked Face Recognition Dataset is Free to Download: https://medium.com/the-programming-hub/wolrds-most-complete-masked-face-recognition-dataset-is-for-free-10d780eed512 ——————————————————————————

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You Can Color Your Grandparent's Old Pictures or Videos with AI DeOldify Tool

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Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models Paper: https://arxiv.org/pdf/2005.07310.pdf Related Codes: https://github.com/airsplay/lxmert https://github.com/ChenRocks/UNITER

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Short over view of Artificial Neural Networks with examples Page: https://www.infinitycodex.in/

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Content-based Image retrieval Paper: https://arxiv.org/abs/2005.02154 Github: https://github.com/PyRetri/PyRetri Installation: https://github.com/PyRetri/PyRetri/blob/master/docs/INSTALL.md