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Computer Science and Programming

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 142 667 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 813-o'rinni va Italiya mintaqasida 86-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 142 667 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.

  • Tasdiqlash holati: Tasdiqlanmagan
  • 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.
  • Tematik yo‘nalishlar: Kontent sellerflash, github, developer, pricing, waybienad kabi asosiy mavzularga jamlangan.

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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 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.

142 667
Obunachilar
-4624 soatlar
-2077 kunlar
-1 28930 kunlar
Postlar arxiv
From command line into a GUI. YOLO demonstration running inside of a PySimpleGUI. Instruction is clearly given in project's github repository

"Advanced Deep Learning with Keras" by Rowel Atienza (Published october, 2018). I am providing this book's github repo for practicing directly with codes. You can learn about key points of Keras and series of GAN. I hope you enjoy

The "Python machine learning book 2nd edition" book code repository. With practical examples and provided Notebook file for convinience

All about GANs: Application area, performance, improvements, difficulties, issues, optimization, ...

Since is introduced by Ian Goodfellow (in 2014), GANs ( Generative Adversarial Networks) gained high attention among AI world and in challenging area of research, as well as, developed many frameworks and cool applications based GANs. Below We share link about list of fraweworks, which created and applied for certain research are based on GANs.

Jupyter Notebook is becoming most dominant IDE for many programming languages (especially, Python). In this link provided useful tips, tricks, and shortcuts about Jupyter Notebook

awesome machine learning Resources list (by language).

"Applied Deep Learning with Python" (august, 2018) GitHub repository

Key Papers in Deep Reinforcement Learning

face-to-edge.gif16.01 MB

Video-to-Video Synthesis. Code by NVIDIA