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Github Top Repositories
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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Mostrar más📈 Análisis del canal de Telegram Github Top Repositories
El canal Github Top Repositories (@githubre) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 13 301 suscriptores, ocupando la posición 15 322 en la categoría Educación y el puesto 32 330 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 13 301 suscriptores.
Según los últimos datos del 12 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 393, y en las últimas 24 horas de 17, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.11%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.75% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 148 visualizaciones. En el primer día suele acumular 100 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 1.
- Intereses temáticos: El contenido se centra en temas clave como repository, fork, programming, statistic, description.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 13 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.
13 301
Suscriptores
+1724 horas
+827 días
+39330 días
Archivo de publicaciones
13 301
🔥 Trending Repository: agents
📝 Description: Intelligent automation and multi-agent orchestration for Claude Code
🔗 Repository URL: https://github.com/wshobson/agents
🌐 Website: https://sethhobson.com
📖 Readme: https://github.com/wshobson/agents#readme
📊 Statistics:
🌟 Stars: 21.9K stars
👀 Watchers: 249
🍴 Forks: 2.5K forks
💻 Programming Languages: Python - Shell
🏷️ Related Topics:
#automation #orchestration #workflows #agents #ai_agents #claude #anthropic #anthropic_claude #claude_code #claudecode #subagents #sub_agents #claudecode_subagents #claudecode_config #claude_code_subagents #claude_code_commands #claude_code_cli #claude_code_plugin #claude_code_plugins #claude_skills================================== 🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: lynx
📝 Description: Empower the Web community and invite more to build across platforms.
🔗 Repository URL: https://github.com/lynx-family/lynx
🌐 Website: https://lynxjs.org
📖 Readme: https://github.com/lynx-family/lynx#readme
📊 Statistics:
🌟 Stars: 13.6K stars
👀 Watchers: 78
🍴 Forks: 472 forks
💻 Programming Languages: C++ - Java - Objective-C - Objective-C++ - Python - TypeScript
🏷️ Related Topics:
#cross_platform================================== 🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: kubernetes
📝 Description: Production-Grade Container Scheduling and Management
🔗 Repository URL: https://github.com/kubernetes/kubernetes
🌐 Website: https://kubernetes.io
📖 Readme: https://github.com/kubernetes/kubernetes#readme
📊 Statistics:
🌟 Stars: 119K stars
👀 Watchers: 3.2k
🍴 Forks: 41.8K forks
💻 Programming Languages: Go - Shell - PowerShell - Makefile - Dockerfile - Python
🏷️ Related Topics:
#go #kubernetes #containers #cncf================================== 🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: ML-For-Beginners
📝 Description: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
🔗 Repository URL: https://github.com/microsoft/ML-For-Beginners
📖 Readme: https://github.com/microsoft/ML-For-Beginners#readme
📊 Statistics:
🌟 Stars: 79.6K stars
👀 Watchers: 1.1k
🍴 Forks: 18.5K forks
💻 Programming Languages: Jupyter Notebook - HTML - Python - Vue - JavaScript - Dockerfile
🏷️ Related Topics:
#python #education #data_science #machine_learning #r #scikit_learn #machine_learning_algorithms #ml #machinelearning #machinelearning_python #scikit_learn_python #microsoft_for_beginners================================== 🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: social-engineer-toolkit
📝 Description: The Social-Engineer Toolkit (SET) repository from TrustedSec - All new versions of SET will be deployed here.
🔗 Repository URL: https://github.com/trustedsec/social-engineer-toolkit
📖 Readme: https://github.com/trustedsec/social-engineer-toolkit#readme
📊 Statistics:
🌟 Stars: 13K stars
👀 Watchers: 645
🍴 Forks: 3.1K forks
💻 Programming Languages: Python - C++ - Shell - C - Java - CSS
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: Foundations-of-LLMs
📝 Description: No description available
🔗 Repository URL: https://github.com/ZJU-LLMs/Foundations-of-LLMs
📖 Readme: https://github.com/ZJU-LLMs/Foundations-of-LLMs#readme
📊 Statistics:
🌟 Stars: 13K stars
👀 Watchers: 157
🍴 Forks: 1.2K forks
💻 Programming Languages: Not available
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: next-ai-draw-io
📝 Description: A next.js web application that integrates AI capabilities with draw.io diagrams. This app allows you to create, modify, and enhance diagrams through natural language commands and AI-assisted visualization.
🔗 Repository URL: https://github.com/DayuanJiang/next-ai-draw-io
🌐 Website: https://next-ai-drawio.jiang.jp/
📖 Readme: https://github.com/DayuanJiang/next-ai-draw-io#readme
📊 Statistics:
🌟 Stars: 3K stars
👀 Watchers: 17
🍴 Forks: 375 forks
💻 Programming Languages: TypeScript - CSS
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.me/DataScienceM
13 301
🔥 Trending Repository: fizzy
📝 Description: Kanban as it should be. Not as it has been.
🔗 Repository URL: https://github.com/basecamp/fizzy
🌐 Website: https://fizzy.do
📖 Readme: https://github.com/basecamp/fizzy#readme
📊 Statistics:
🌟 Stars: 2.4K stars
👀 Watchers: 27
🍴 Forks: 299 forks
💻 Programming Languages: Ruby - HTML - CSS - JavaScript
🏷️ Related Topics:
#ruby #rails #kanban #hotwire================================== 🧠 By: https://t.me/DataScienceM
13 301
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13 301
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13 301
🔥 Trending Repository: Memori
📝 Description: Open-Source Memory Engine for LLMs, AI Agents & Multi-Agent Systems
🔗 Repository URL: https://github.com/MemoriLabs/Memori
🌐 Website: https://memorilabs.ai
📖 Readme: https://github.com/MemoriLabs/Memori#readme
📊 Statistics:
🌟 Stars: 8.8K stars
👀 Watchers: 46
🍴 Forks: 629 forks
💻 Programming Languages: Python - PLpgSQL
🏷️ Related Topics:
#python #agent #awesome #state_management #ai #memory #memory_management #hacktoberfest #long_short_term_memory #rag #llm #memori_ai #hacktoberfest2025 #chatgpt #aiagent================================== 🧠 By: https://t.me/DataScienceM
13 301
+2
A new Python library for agent-based data-processing and ETL using AI has been released.
Introducing DocETL.
What is important to know:
1. What is DocETL?
It is a tool for creating and running data pipelines, especially well-suited for complex document processing.
It includes:
- interactive UI playground
- Python package for running pipelines in production
2. DocWrangler
DocWrangler helps gradually build the pipeline:
- trying different prompts and viewing results in real-time
- building the pipeline step by step
- exporting the final configuration for production
3. Python package DocETL
It is used for running pipelines in production. In the example, a pipeline is created that analyzes medical transcripts, identifies drug names, normalizes similar names, and generates summaries of side effects and areas of application.
More information: https://github.com/ucbepic/docetl
👉 https://t.me/DataScienceN
13 301
👨💻 Wren AI
🛠 Wren AI is an AI agent that allows users to request data in natural language and receive accurate SQL queries, charts, and analytical reports within seconds.
🔰 It provides capabilities for data interaction, insight generation, and includes a semantic layer that ensures the accuracy of conclusions.
🔰 API integration enables the creation of custom agents and chatbots.
🌟 The platform supports multiple databases and is compatible with various LLM models.
🔗 Links:
https://github.com/Canner/WrenAI
🖤Tags: #ai #agents #sql #llm
13 301
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13 301
🌆 RMBG
🛠️ RMBG is a new AI background removal model that significantly outperforms its counterparts.
🔰 It effectively separates the foreground and background for various types of images, providing high accuracy and commercial applicability.
🔗Links:
https://github.com/Bria-AI/RMBG-2.0/
🏷️Tags:
#ai #imageeditor
13 301
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13 301
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13 301
If you love automating everything, this is for you
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👉 https://t.me/DataScienceN
