Computer Science and Programming
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
Ko'proq ko'rsatish
Tarmoq:📈 Telegram kanali Computer Science and Programming analitikasi
Computer Science and Programming (@computer_science_and_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 140 509 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 802-o'rinni va Italiya mintaqasida 88-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 140 509 obunachiga ega bo‘ldi.
30 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -752 ga, so‘nggi 24 soatda esa -56 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 7.74% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.89% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 10 875 marta ko‘riladi; birinchi sutkada odatda 2 656 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 14 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent sellerflash, github, developer, pricing, waybienad kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
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 31 Avgust, 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.
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.🔗 https://blog.platformatic.dev/seamlessly-blend-php-with-nodejs
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.🔗 https://platejs.org/
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.🔗 https://amigoscode.com/blogs/how-netflix-uses-java-to-stream-to-200m-users
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.🔗 https://llm-ui.com/
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.🔗 https://devjournal.info/minio-aws-s3-but-free-and-open-source/
