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Firibgarlarga uchmang! Telemetrio bunday kanallarni topadi va belgilaydi πŸ‘‰ Belgini koβ€˜rmoqchi boβ€˜lsangiz, obuna boβ€˜ling

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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πŸ“ˆ Telegram kanali Computer Science and Programming analitikasi

Computer Science and Programming (@computer_science_and_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 138 978 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 815-o'rinni va Italiya mintaqasida 88-o'rinni egallagan.

πŸ“Š Auditoriya koβ€˜rsatkichlari va dinamika

Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ sanasidan buyon loyiha tez oβ€˜sib, 138 978 obunachiga ega boβ€˜ldi.

29 Oktabr, 2026 dagi oxirgi ma’lumotlarga koβ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -769 ga, soβ€˜nggi 24 soatda esa -80 ga oβ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oβ€˜rtacha 9.31% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.76% ini tashkil etuvchi reaksiyalarni toβ€˜playdi.
  • Post qamrovi: Har bir post oβ€˜rtacha 12 946 marta koβ€˜riladi; birinchi sutkada odatda 2 442 ta koβ€˜rish yigβ€˜iladi.
  • Reaksiyalar va oβ€˜zaro ta’sir: Auditoriya faol: har bir postga oβ€˜rtacha 31 ta reaksiya keladi.
  • Tematik yoβ€˜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:
β€œChannel 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 30 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boβ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini koβ€˜rsatadi.

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138 978
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Postlar arxiv
Seamlessly Blend PHP with Node.js TLDR Platformatic introduces php-node, a Node.js module that allows developers to embed PHP
Seamlessly Blend PHP with Node.js
TLDR Platformatic introduces php-node, a Node.js module that allows developers to embed PHP within Node.js applications. The module utilizes Rust to execute PHP applications in a multi-threaded environment, providing enhanced performance and seamless integration. Key features include seamless integration, multi-threaded processing, improved performance, and a unified development environment. Use cases range from migrating legacy PHP apps to building hybrid applications. The post also provides examples of running PHP and WordPress inside a Node.js server.
πŸ”— https://blog.platformatic.dev/seamlessly-blend-php-with-nodejs

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Plate - Rich-text editor with AI, MCP, and shadcn/ui TLDR Plate Create blockquotes to emphasize important information or high
Plate - Rich-text editor with AI, MCP, and shadcn/ui
TLDR Plate Create blockquotes to emphasize important information or highlight quotes from external sources. This is suitable for certain scenarios, there are times when you want users to be able to paste content while preserving its formatting. To achieve this, your editor should be capable of handling 'text/html' data.
πŸ”— https://platejs.org/

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How Netflix Uses Java to Stream to 200M+ Users TLDR Netflix uses Java to manage a complex backend that streams 250 million ho
How Netflix Uses Java to Stream to 200M+ Users
TLDR Netflix uses Java to manage a complex backend that streams 250 million hours of content daily. They transitioned from a monolithic architecture to microservices, leveraging Java for its concurrency, scalability, and rich ecosystem. Influential tools developed by Netflix include Eureka for service discovery and Hystrix for fault tolerance, which are integrated with Java to optimize performance and reliability across their AWS platform. Their approach and contributions have significantly impacted modern backend systems.
πŸ”— https://amigoscode.com/blogs/how-netflix-uses-java-to-stream-to-200m-users

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React library for LLMs TLDR llm-ui is a React library that provides UI components for integrating Large Language Models into
React library for LLMs
TLDR llm-ui is a React library that provides UI components for integrating Large Language Models into web applications. It works universally with any LLM model by operating on the model's output string, supporting popular services like ChatGPT, Claude, Ollama, Mistral, Hugging Face, and LangChain. The library aims to simplify the process of displaying LLM responses in React-based user interfaces.
πŸ”— https://llm-ui.com/

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MinIO: AWS S3, but free and open-source TLDR MinIO offers an open-source, high-performance alternative to AWS S3 for object s
MinIO: AWS S3, but free and open-source
TLDR MinIO offers an open-source, high-performance alternative to AWS S3 for object storage, ideal for indie developers and small teams due to its cost-effective scalability and flexibility. With features like bucket organization, IAM policies, event hooks, and multi-platform hosting options, MinIO can operate across local machines, Docker, Kubernetes, and cloud VMs. While it eliminates vendor lock-in and incurs no direct usage fees, MinIO does require responsible management of infrastructure for backups and high availability.
πŸ”— https://devjournal.info/minio-aws-s3-but-free-and-open-source/

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Nvidia adds native Python support to CUDA πŸ”— https://thenewstack.io/nvidia-finally-adds-native-python-support-to-cuda/
Nvidia adds native Python support to CUDA πŸ”— https://thenewstack.io/nvidia-finally-adds-native-python-support-to-cuda/