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
Mostrar más📈 Análisis del canal de Telegram Computer Science and Programming
El canal Computer Science and Programming (@computer_science_and_programming) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 142 827 suscriptores, ocupando la posición 814 en la categoría Tecnologías y Aplicaciones y el puesto 86 en la región Italia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 142 827 suscriptores.
Según los últimos datos del 11 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -1 293, y en las últimas 24 horas de -44, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.75%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.81% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 8 214 visualizaciones. En el primer día suele acumular 2 581 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 15.
- Intereses temáticos: El contenido se centra en temas clave como sellerflash, github, developer, pricing, waybienad.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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...”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 12 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
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.
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.
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 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.
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.
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.
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
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.
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.
DynaUI is a React component library featuring 30+ animated components built with Tailwind CSS and Framer Motion. It promises to reduce development time from weeks to hours by providing pre-built, customizable UI components for landing pages and web applications. The library has received positive feedback from developers who appreciate its time-saving potential and quality animations.
Self-hosting offers developers a unique opportunity to gain in-depth knowledge of software operations beyond basic development tasks. It involves learning about networking, system administration, security, and DevOps. Engaging in self-hosting can build confidence, improve problem-solving skills, and open up career opportunities in cloud infrastructure. The post encourages developers to start small with easy-to-manage services, emphasizing the educational value of practical experience.
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