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 140 441 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 804-o'rinni va Italiya mintaqasida 88-o'rinni egallagan.

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невідомо sanasidan buyon loyiha tez o‘sib, 140 441 obunachiga ega bo‘ldi.

31 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -734 ga, so‘nggi 24 soatda esa -18 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

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Jalb etish (ER): Auditoriya o‘rtacha 7.96% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.94% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 11 177 marta ko‘riladi; birinchi sutkada odatda 2 728 ta ko‘rish yig‘iladi.
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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_sc...”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 01 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.

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Postlar arxiv

140 427

NeurIPS 2020 highlights at: https://crossminds.ai/category/neurips%202020/ Also follow recent conferences and discover your inspirations and see what's happening

140 427

NeurIPS 2020 is the largest machine learning conference and is just around the corner! Check out this exclusive collection of 100+ pre-recorded talks on the latest machine learning research from world-renowned tech companies and universities. Videos are shared by the authors with free public access

140 427

Project page: https://video-nerf.github.io/ Paper: https://arxiv.org/pdf/2011.12950.pdf Code: coming soon

140 427

3D photo is great, but have you ever seen 3D *free-viewpoint video*? Space-time neural rendering from a single, casually captured video! https://youtu.be/2tN8ghNu2sI

140 427

https://laconicml.com/coursera-artificial-intelligence-courses/?fbclid=IwAR2UlS5rr5ya9f3YtxQFdyQnA69ll-m3xTN5kdQVaiUpRp5nkaIyOuq5e8g Yann LeCun’s Deep Learning Course at CDS also free now: https://cds.nyu.edu/deep-learning/

140 427

Top 40 COMPLETELY FREE Coursera Artificial Intelligence and Computer Science Courses

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https://medium.com/the-innovation/130-machine-learning-projects-solved-and-explained-605d188fb392

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Top deep learning Github repositories https://github.com/mbadry1/Top-Deep-Learning

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List of top 200 deep learning Github repositories sorted by the number of stars.

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Rotated Binary Neural Network Github (Pytorch implementation): https://github.com/lmbxmu/RBNN Paper: https://arxiv.org/abs/2009.13055

140 427

Binary Neural Network (BNN) is best feet for reducing the complexity of deep neural networks. But, it suffers severe performance degradation. Rotation based training leads to around 50% weight flips which maximize the information gain and showed state-of-the-arts in benchmark datasets Rotated Binary Neural Network (RBNN)

140 427

https://github.com/brinesoftwares/Flutter-AI-Rubik-cube-Solver?fbclid=IwAR0agon7_lmFDOoBeT3ru9skWvTer3syzLFz_vHDZy9isC3FzWTJJ3JufsE

140 427

AI based Rubik's Cube Solver using Flutter and Python

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https://www.nature.com/articles/s41586-020-2649-2

140 427

NumPy provides an easily readable, expressive, high-level API for array programming. It takes care of the underlying mechanics that make operations fast.

140 427

https://dafriedman97.github.io/mlbook/content/table_of_contents.html And The list of Most Updated and Free Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Mathematics, Python Programming Resources. (Last Update: Sept 9, 2020): https://www.marktechpost.com/free-resources/?fbclid=IwAR0hc2qkxPMXhQGzsg07ffgFecRr01tSCRqlhb_XMR6PjPt1KNdy68cLy9w

140 427

Here is a new, and free book on Machine Learning from scratch. It includes the math and code examples. Solid reference.

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Organize the daily influx of ML content in meaningful ways without feeling overwhelmed, By Goku Mohandas et al. : https://madewithml.com/collections/

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Brian Huge, Antoine Savine : https://arxiv.org/abs/2005.02347 TF1 implementation notebook on Colab: https://colab.research.google.com/github/differential-machine-learning/notebooks/blob/master/DifferentialML.ipynb