Artificial Intelligence && Deep Learning

الذهاب إلى القناة على Telegram

Channel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:

📈 نظرة تحليلية على قناة تيليجرام Artificial Intelligence && Deep Learning

تُعد قناة Artificial Intelligence && Deep Learning (@deeplearning_ai) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 58 023 مشتركاً، محتلاً المرتبة 2 289 في فئة التكنولوجيات والتطبيقات والمرتبة 6 003 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 58 023 مشتركاً.

بحسب آخر البيانات بتاريخ 24 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -193، وفي آخر 24 ساعة بمقدار 17، مع بقاء الوصول العام مرتفعاً.

حالة التحقق: غير موثّقة
معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 9.42‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً N/A‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
وصول المنشورات: يحصل كل منشور على متوسط 5 467 مشاهدة. وخلال اليوم الأول يجمع عادةً 0 مشاهدة.
التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 16.
الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل github, learning, estimation, dataset, engineer.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Channel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:”

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 25 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

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المشتركون

+1724 ساعات

-237 أيام

-19330 أيام

5 467

عرض المشاهدات

لا توجد بيانات24 ساعات

لا توجد بيانات48 ساعات

9.42%

معدل المشاركة

لا توجد بيانات

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Hey if you are interested in learning data science, machine learning, deep learning or Big data. You will also get to know how to do career transition to data science field. In this telegram group, you will get daily practice quizzes on interview questions, study materials, cheatsheets, blogs, books for free. Here is the telegram group that you can join https://t.me/dataspoof

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Swin Transformer for Object Detection PAPER: Swin Transformer: Hierarchical Vision Transformer using Shifted Windows VIDEO: https://www.youtube.com/watch?v=FQVS_0Bja6o CODE: https://github.com/SwinTransformer/Swin-Transformer-Object-Detection @deeplearning_ai

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Free Hands-on Demo Session organized by Management Career Institute Topic: Application of AI in price prediction. Deliverables: -Basic of data handling part. -Introducing to forecasting models. -Introducing Deep learning based forecast. -Explaining detailed architecture of the DL model. -Implementing live on real time dataset. Duration - 2 hours Date - Thursday | 29th July Time - 6.30 PM IST (Evening Slot) Live Hands-on Session Get Register Now: https://forms.gle/fkRv6dJnymew6sk6A Who will be Instructor? Instructor is Lead of Automation (Data Science & Artificial Intelligence) at Wipro. He has solved 60+ Research use cases, published 45+ Patents (received 23 grants) across various countries. He is also a Member of Advisory council at India ka AI.

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A simpler design but better performance! It aims to bridge the gap between research and industrial communities. Paper: https://arxiv.org/pdf/2107.08430v1.pdf Github: https://github.com/Megvii-BaseDetection/YOLOX t.me/deeplearning_ai

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YOLOX: Exceeding YOLO Series in 2021 Anchor-free version of YOLO series Won the 1st Place on Streaming Perception Challenge (Workshop on Autonomous Driving at CVPR 2021) t.me/deeplearning_ai

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Various Types of Neural Networks

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💡AI Workshop: Bring Your Use Case Ideas to Life 💡 👍In this online workshop, we present how you can use AI services and start prototyping in minutes. 👍We cover some of the most popular AI verticals such as Computer Vision and Natural Language Processing. After this workshop, you will know: 1. What is AI as a Service, and how does it work? 2. What are Computer Vision, NLP, and Speech? 3. How can you prototype your AI products before actual implementation? Requirements: ✅ Free Registration ✅ Basic Python knowledge 👉16 July, 17:00 - 18:00 CET👈 https://www.linkedin.com/events/6814928657631473664/

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GIRAFFE: A Closer Look at the Code for CVPR 2021’s Best Paper [Blog] https://autonomousvision.github.io/giraffe/ [Paper] http://www.cvlibs.net/publications/Niemeyer2021CVPR.pdf [Source] https://github.com/autonomousvision/giraffe [Interactive slides] https://m-niemeyer.github.io/slides/#/4 [Collected] https://m-niemeyer.github.io/project-pages/giraffe/index.html https://t.me/DeepLearning_ai

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GIRAFFE: A Closer Look at the Code for CVPR 2021’s Best Paper [Paper] http://www.cvlibs.net/publications/Niemeyer2021CVPR.pdf [Source] https://github.com/autonomousvision/giraffe [Blog] https://autonomousvision.github.io/giraffe/ [Interactive slides] https://m-niemeyer.github.io/slides/#/4 [Collected] https://m-niemeyer.github.io/project-pages/giraffe/index.html https://t.me/DeepLearning_ai

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https://t.me/DeepLearning_ai

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GIRAFFE: A Closer Look at the Code for CVPR 2021’s Best Paper [Paper] http://www.cvlibs.net/publications/Niemeyer2021CVPR.pdf [Source] https://github.com/autonomousvision/giraffe [Blog] https://autonomousvision.github.io/giraffe/ [Interactive slides] https://m-niemeyer.github.io/slides/#/4 [Collected] https://m-niemeyer.github.io/project-pages/giraffe/index.html https://t.me/DeepLearning_ai

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Probabilistic two-stage detection Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network. github: https://github.com/xingyizhou/CenterNet2?utm_source=catalyzex.com paper: https://arxiv.org/pdf/2103.07461.pdf https://t.me/DeepLearning_ai