ar
Feedback
Computer Science and Programming

Computer Science and Programming

الذهاب إلى القناة على Telegram

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

إظهار المزيد

📈 نظرة تحليلية على قناة تيليجرام Computer Science and Programming

تُعد قناة Computer Science and Programming (@computer_science_and_programming) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 140 524 مشتركاً، محتلاً المرتبة 804 في فئة التكنولوجيات والتطبيقات والمرتبة 88 في منطقة إيطاليا.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 140 524 مشتركاً.

بحسب آخر البيانات بتاريخ 29 أغسطس, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -741، وفي آخر 24 ساعة بمقدار -33، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 7.84‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.89‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 11 021 مشاهدة. وخلال اليوم الأول يجمع عادةً 2 656 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 14.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل sellerflash, github, developer, pricing, waybienad.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
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...

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 30 أغسطس, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

Buy Ad
140 524
المشتركون
-3324 ساعات
-2907 أيام
-74130 أيام
أرشيف المشاركات
✅ Hi everyone, from now on Computer Science is on WhatsApp too. Subscribe if you prefer reading news there 👇🏻👇🏻 ‎https://whatsapp.com/channel/0029Vb6WuS94yltPj2RZuP11

Design patterns for agentic AI The era of agentic AI has begun, with intelligent agents increasingly handling tasks and makin
Design patterns for agentic AI
The era of agentic AI has begun, with intelligent agents increasingly handling tasks and making decisions autonomously, boosting productivity. This webinar explores how these AI systems, differing from traditional SaaS tools, are built using agentic design patterns. It covers why legacy architectures are inadequate and demonstrates how platforms like Akka enable building scalable, event-driven AI agents.

kepano/defuddle: Extract the main content from web pages. Defuddle is a tool designed to extract the main content from web pa
kepano/defuddle: Extract the main content from web pages.
Defuddle is a tool designed to extract the main content from web pages by removing unnecessary elements like comments, sidebars, and headers. It creates clean HTML documents suitable for HTML-to-Markdown conversion and was intended for use with the Obsidian Web Clipper. Defuddle can serve as a replacement for Mozilla Readability, provides consistent outputs for various elements, and extracts metadata using schema.org. Installation requires npm and for Node.js, JSDOM. The tool is available in core, full, and Node.js bundles and offers configurable options for parsing and content manipulation.

How WhatsApp Handles 40 Billion Messages Per Day WhatsApp manages to handle nearly 40 billion daily messages by utilizing a r
How WhatsApp Handles 40 Billion Messages Per Day
WhatsApp manages to handle nearly 40 billion daily messages by utilizing a robust backend architecture with simplicity, asynchronicity, and isolation at its core. Erlang is pivotal, offering lightweight concurrency, fault isolation, and efficient message routing. The architecture benefits from smart partitioning, resiliency under failures, seamless upgrades, and focused quality control, all managed by a small engineering team. Database design favors speed with in-memory key-value stores and async writes, while backend systems are structurally isolated to ensure reliability. 

How AI Vibe Coding Is Destroying Junior Developers' Careers Vibe coding, where developers use AI to build entire applications
How AI Vibe Coding Is Destroying Junior Developers' Careers
Vibe coding, where developers use AI to build entire applications without writing code themselves, is creating a generation of pseudo-developers who lack fundamental programming skills. Research shows AI tools actually decrease productivity by 19% for experienced developers, while security vulnerabilities plague AI-generated code. Junior developers using this approach become dependent on AI for debugging and maintenance, making them less competitive in an already brutal job market where 94,000 tech workers have been laid off. The practice creates massive technical debt and prevents skill development, ultimately harming career prospects rather than helping them.

Bye bye schema coupling, hello semantic coupling The post introduces the concept of semantic coupling as an innovative method
Bye bye schema coupling, hello semantic coupling
The post introduces the concept of semantic coupling as an innovative method to manage schema evolution in event-driven architectures, replacing traditional schema coupling. By using semantic tags instead of versioning or altering event schemas, it allows consumers to focus on the meaning of data rather than its representation. This approach prevents breaking changes and eliminates the need for event versioning, encouraging smoother schema transitions. Tools like Orbital and Taxi can facilitate these transformations by decoupling the data representation from consumers

System broke. I led. Now it scales to millions users… A technical lead shares their experience rebuilding a failing e-commerc
System broke. I led. Now it scales to millions users…
A technical lead shares their experience rebuilding a failing e-commerce system in 30 days, transforming it from a single-server monolith to a scalable microservices architecture. The rebuild involved migrating to Google Cloud Platform with Kubernetes, breaking down the Node.js monolith into Java and Go microservices, implementing Redis caching and Kafka for background jobs, rebuilding the frontend with Next.js, and adding comprehensive monitoring. The result was a system that could handle 50K concurrent users with 3x faster response times and reduced page load times from 3.7s to 1.2s. 

schej-it/schej.it: Schej is a scheduling platform helps you find the best time for a group to meet. It is a free availability
schej-it/schej.it: Schej is a scheduling platform helps you find the best time for a group to meet. It is a free availability poll that is easy to use and integrates with your calendar.
Schej is an inclusive scheduling platform designed to help groups find optimal meeting times. It offers free availability polling, integrates with various calendar systems, and supports features like time zone management and email notifications. Built with Vue 2, MongoDB, Go, and TailwindCSS, it provides functionality to match availabilities, duplicate polls, and export data in CSV format.

Build an MCP Server in 3 Steps This post describes a simple three-step process to build an MCP server using tools like Giting
Build an MCP Server in 3 Steps
This post describes a simple three-step process to build an MCP server using tools like Gitingest and Google AI Studio, enabling the transformation of FastMCP repository data into LLM-readable text. It also highlights the capabilities of the Firecrawl framework, which converts websites into structured formats for AI applications.

⚠ Message was hidden by channel owner
⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner
⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner
⚠ Message was hidden by channel owner

Hello, Typesense Typesense is presented as an approachable search engine that makes advanced search functionality accessible
Hello, Typesense
Typesense is presented as an approachable search engine that makes advanced search functionality accessible to developers. The introduction emphasizes how Typesense eliminates the confusion and frustration often associated with search tools, making developers feel capable rather than overwhelmed. A comprehensive 22-episode series covers everything from basic queries and setup to advanced features like semantic search, vector queries, and cloud deployment.

Frontend Isn't Just UI Frontend engineering goes beyond styling buttons and layouts; it involves building systems that serve
Frontend Isn't Just UI
Frontend engineering goes beyond styling buttons and layouts; it involves building systems that serve human experiences. Key aspects include data flow, state models, component architecture, user experience flow, and accessibility. It combines design with logic to create scalable and user-friendly products.

⚠ Message was hidden by channel owner
⚠ Message was hidden by channel owner

evroon/bracket: Selfhosted tournament system Bracket is a self-hosted tournament system designed for easy use, leveraging asy
evroon/bracket: Selfhosted tournament system
Bracket is a self-hosted tournament system designed for easy use, leveraging async Python with FastAPI for the backend and Next.js with Mantine for the frontend. It supports various tournament formats such as single elimination, round-robin, and swiss, and allows for dynamic scheduling and management of tournaments and teams. The system can be run using Docker or independently with pipenv and yarn, and is configured using .env files or environment variables.

The AI Engineering Stack AI engineering has emerged as a distinct discipline built on three layers: application development,
The AI Engineering Stack
AI engineering has emerged as a distinct discipline built on three layers: application development, model development, and infrastructure. Unlike traditional ML engineering which focuses on training custom models, AI engineering emphasizes adapting existing foundation models through prompt engineering and fine-tuning. The field requires less deep ML knowledge but more focus on evaluation, inference optimization, and building user interfaces. AI engineers work with larger, more compute-intensive models that produce open-ended outputs, making evaluation significantly more challenging. The role bridges software engineering and ML, with many practitioners coming from full-stack development backgrounds rather than traditional ML research. 

Blob shape with hover effect Learn how to use the CSS-only shape() function to create a dynamic blob shape with a hover effec
Blob shape with hover effect
Learn how to use the CSS-only shape() function to create a dynamic blob shape with a hover effect. The code is accessible via an online generator, but it currently works only in Chrome.
css-tip.com

The Curse of Microlearning Microlearning, a method of delivering knowledge in concise formats like book summaries or fact-of-
The Curse of Microlearning
Microlearning, a method of delivering knowledge in concise formats like book summaries or fact-of-the-day apps, is critiqued for its ineffectiveness in providing deep understanding and valuable insights. This approach reduces complex concepts into simplistic bites, which can lead to uniformity in thought and diminish the appreciation for unique writing styles. For deep comprehension and engagement, longer, more detailed exploration of material is necessary.

Tools I Use Every Day (June 2025 Edition) A comprehensive overview of daily development tools used by a professional develope
Tools I Use Every Day (June 2025 Edition)
A comprehensive overview of daily development tools used by a professional developer, covering code editors (JetBrains Rider, VS Code), collaboration platforms (GitHub, Teams, Slack, Discord), productivity apps (Notion, ChatGPT, Feedly), AI tools (LM Studio, Azure Local AI Foundry), and utilities (Windows Terminal, Postman, NordPass). Includes cost breakdown showing monthly expenses ranging from $50-100+ depending on licensing tiers, with many tools offering free alternatives.