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Github Top Repositories

Github Top Repositories

الذهاب إلى القناة على Telegram

Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.

إظهار المزيد

📈 نظرة تحليلية على قناة تيليجرام Github Top Repositories

تُعد قناة Github Top Repositories (@githubre) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 13 354 مشتركاً، محتلاً المرتبة 15 230 في فئة التعليم والمرتبة 31 848 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 13 354 مشتركاً.

بحسب آخر البيانات بتاريخ 18 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 431، وفي آخر 24 ساعة بمقدار 13، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 1.06‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 0.78‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 142 مشاهدة. وخلال اليوم الأول يجمع عادةً 104 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 1.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل repository, fork, programming, statistic, description.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 19 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

13 354
المشتركون
+1324 ساعات
+757 أيام
+43130 أيام
أرشيف المشاركات
😍😍😍😍😍😍😍😍 It’s truly fascinating — definitely worth diving deeper into and working on! 😍😍😍😍😍😍😍😍

🔖 ImageBind: One Embedding Space To Bind Them All 📝 This project is a significant step forward in understanding and connect
🔖 ImageBind: One Embedding Space To Bind Them All 📝 This project is a significant step forward in understanding and connecting information from diverse sources like images, text, audio, video, and even motion sensor data. ⚙️ Supports 6 Modalities: 📷 Image 📝 Text 🔈 Audi 🎥 Video 🦴 IMU sensor data (e.g., accelerometer) 🙄 Depth/Thermal & 3D data Interestingly, only some modalities had labels, yet ImageBind learned to align them through self-supervised learning. 💫 Key Features: ..No need for paired data (e.g., images and audio don’t have to be aligned)..Leverages contrastive learning for learning joint embedding space ..Competes with CLIP and AudioCLIP, but with better accuracy and coverage..Enables zero-shot retrieval (e.g., finding relevant video using just a sentence) 📌 Repo: https://github.com/facebookresearch/ImageBind 🔍 By: https://t.me/DataScienceN 🌟 #ImageBind #MultimodalAI #MetaAI #DeepLearning #SelfSupervised

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🔖 Project name : Analysis of Covid-19 chest x-rays 📝 In order to diagnose patients with Covid-19, the analysis of chest X-r
🔖 Project name : Analysis of Covid-19 chest x-rays 📝 In order to diagnose patients with Covid-19, the analysis of chest X-rays is a possibility to be explored to more easily detect positive cases. If the classification through deep learning of such data proves effective in detecting positive cases, then this method can be used in hospitals and clinics when traditional testing cannot be done. 📌 Repo: https://github.com/rehabaam/ds_covid19_project 🔍 By: https://t.me/DataScienceN 🌟

📌 Project name: Cat/Dog/Fox Lightning 2024 By: https://t.me/DataScienceN 🌟

📌 Project name: Cat/Dog/Fox Lightning 2024 📝 Language: #Python 🔗 Dataset Link: https://www.kaggle.com/datasets/snmahsa/ani
📌 Project name: Cat/Dog/Fox Lightning 2024 📝 Language: #Python 🔗 Dataset Link: https://www.kaggle.com/datasets/snmahsa/animal-image-dataset-cats-dogs-and-foxes 🖋 Download the dataset offline: https://t.me/datasets1/668

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