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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.
Больше📈 Аналитический обзор Telegram-канала Github Top Repositories
Канал Github Top Repositories (@githubre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 13 330 подписчиков, занимая 15 272 место в категории Образование и 32 126 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 13 330 подписчиков.
Согласно последним данным от 15 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 413, а за последние 24 часа — 8, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.07%. В первые 24 часа после публикации контент обычно набирает 0.79% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 143 просмотров. В течение первых суток публикация набирает 105 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 1.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как repository, fork, programming, statistic, description.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Благодаря высокой частоте обновлений (последние данные получены 16 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
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Подписчики
+824 часа
+927 дней
+41330 день
Архив постов
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
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Imagine an AI assistant for data scientists that builds an entire Jupyter notebook on request
Data Copilot - is like Cursor, but it is designed for working with data📊
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Some projects don’t scream for attention — they quietly change the way we learn🧑🎓.
Python Data Science Handbook is one of them📖.
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A powerful open-source GitHub repository by Jake VanderPlas. It turns his bestselling book into interactive Jupyter notebooks that teach: 🧮 NumPy → fast array operations 📊 Pandas → data cleaning & analysis 📈 Matplotlib → clear visualizations 🤖 Scikit-learn → machine learning made simple 🛸 IPython → efficient coding environment🎚️Run everything instantly via Binder or Google Colab — no setup needed⚙.
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Repost from Machine Learning with Python
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Repost from Machine Learning with Python
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🚀 Master Python with Ease!
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💃 GENMO: Generalist Human Motion by NVIDIA 💃
NVIDIA introduces GENMO, a unified generalist model for human motion that seamlessly combines motion estimation and generation within a single framework. GENMO supports conditioning on videos, 2D keypoints, text, music, and 3D keyframes, enabling highly versatile motion understanding and synthesis.
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Repost from Machine Learning with Python
🎯 ابدأ رحلتك الاحترافية في البرمجة مع
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🔥Powerful Combo: Ultralytics YOLO11 + Sony Semicon | AITRIOS (Global) Platform + Raspberry Pi
We’ve recently updated our Sony IMX model export to fully support YOLO11n detection models! This means you can now seamlessly run YOLO11n models directly on Raspberry Pi AI Cameras powered by the Sony IMX500 sensor — making it even easier to develop advanced Edge AI applications. 💡
To test this new export workflow, I trained a model on the VisDrone dataset and exported it using the following command:
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yolo export model=<path_to_drone_model> format=imx data=VisDrone.yaml
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Sure! Here's the English version of your post, translated naturally and professionally:
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🔥 Powerful Combo: Ultralytics YOLO11 + Sony Semicon | AITRIOS (Global) Platform + Raspberry Pi
We’ve recently updated our Sony IMX model export to fully support YOLO11n detection models! This means you can now seamlessly run YOLO11n models directly on Raspberry Pi AI Cameras powered by the Sony IMX500 sensor — making it even easier to develop advanced Edge AI applications. 💡
To test this new export workflow, I trained a model on the VisDrone dataset and exported it using the following command:
👉
yolo export model=<path_to_drone_model> format=imx data=VisDrone.yaml13 330
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
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7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
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Follow me on LinkedIn for more projects and jobs
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Repost from Machine Learning with Python
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Repost from Python Courses & Resources
🎁 Your balance is credited $4,000 , the owner of the channel wants to contact you!
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