Github Top Repositories
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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Показати більше📈 Аналітичний огляд Telegram-каналу Github Top Repositories
Канал Github Top Repositories (@githubre) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 15 274 підписників, посідаючи 13 395 місце в категорії Освіта та 25 969 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 15 274 підписників.
За останніми даними від 11 листопада, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 339, а за останні 24 години на 9, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 0.88%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.61% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 134 переглядів. Протягом першої доби публікація в середньому набирає 93 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 1.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як repository, fork, programming, statistic, description.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Завдяки високій частоті оновлень (останні дані отримано 12 листопада, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.
15 274
Підписники
+924 години
+587 днів
+33930 днів
Архів дописів
15 275
🔥 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
15 275
🔥 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
15 275
🔥 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
15 275
🔥 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
15 275
🔥 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
15 275
🔥 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
15 275
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15 275
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15 275
🔥 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
15 275
+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
15 275
👨💻 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:
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🖤Tags: #ai #agents #sql #llm
15 275
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15 275
🌆 RMBG
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🔰 It effectively separates the foreground and background for various types of images, providing high accuracy and commercial applicability.
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🏷️Tags:
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15 275
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👉 https://t.me/DataScienceN
15 275
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