AI and Machine Learning
Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses
Mostrar más📈 Análisis del canal de Telegram AI and Machine Learning
El canal AI and Machine Learning (@machine_learning_courses) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 93 845 suscriptores, ocupando la posición 1 577 en la categoría Educación y el puesto 3 133 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 93 845 suscriptores.
Según los últimos datos del 16 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 1 150, y en las últimas 24 horas de 20, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 9.72%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.61% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 9 118 visualizaciones. En el primer día suele acumular 2 449 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 14.
- Intereses temáticos: El contenido se centra en temas clave como learning, llm, linkedin, linux, udemy.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more!
Buy ads: https://telega.io/c/machine_learning_courses”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 17 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 Educación.
📔 Understand how LLMs actually work under the hood from scratch with practical and fun lessons. No prior knowledge required!🎙 Taught by: Scott Kerr 🌟 ZTM Link 📤 Download All Courses
fast-agent is a modern framework for rapid development and testing of intelligent agents and workflows supporting the MCP (Model-Context-Protocol) protocol. It provides a simple declarative syntax and powerful tools for building multi-agent systems with support for OpenAI, Anthropic, and other models.
▪️ Main features
• Fast agent creation using @fast.agent decorators, minimizing code amount.
• Workflow support: chains (chain), parallel calls (parallel), routers (router), orchestrators (orchestrator), evaluation and optimization schemes (evaluator_optimizer).
• Multimodality: processing images, PDF files, and integration with external MCP resources.
• Interactive debugging: configuration and diagnostics of agents before, during, and after workflow execution.
• Flexible configuration via fastagent.config.yaml and fastagent.secrets.yaml.
• Integration with LLMs: OpenAI (GPT-4 and others), Anthropic (Haiku, Sonnet, Opus), and other models through MCP servers.
▪️ Quick start
1️⃣ Install the uv package manager for Python.
2️⃣ Install fast-agent:
uv pip install fast-agent-mcp
3️⃣ Create a sample agent and configuration files:
uv run fast-agent setup
4️⃣ Run the agent:
uv run agent.py
5️⃣ To run workflow examples:
uv run fast-agent quickstart workflow
▪️ Documentation and examples
• Official website: [fast-agent.ai](https://fast-agent.ai)
• Documentation: [fast-agent-docs](https://github.com/evalstate/fast-agent-docs)
• Examples: examples directory in the repository.
▪️ Community and development
• The project is actively developed, ⭐️ 1.7k+ stars on GitHub.
• Discussions: [Discussions](https://github.com/evalstate/fast-agent/discussions)
• Latest releases: [Releases](https://github.com/evalstate/fast-agent/releases)
▪️ Video review
[First Look at Fast-Agent (or Manus) – Coding an AI ...](https://www.youtube.com/watch?v=GaVQyYougPc&utm_source=chatgpt.com)
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