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 142 711 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, 142 711 obunachiga ega bo‘ldi.

15 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -1 289 ga, so‘nggi 24 soatda esa -46 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

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Jalb etish (ER): Auditoriya o‘rtacha 6.44% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.85% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 9 197 marta ko‘riladi; birinchi sutkada odatda 2 646 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 17 ta reaksiya keladi.
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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 16 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.

142 711

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-4624 soatlar

-2077 kunlar

-1 28930 kunlar

9 197

Post ko'rishlar

~ 2 64624 soatlar

~ 3 57748 soatlar

6.44%

Muloqot nisbati

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Postlar arxiv

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.

142 697

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

142 697

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