اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Artificial Intelligence && Deep Learning
رفتن به کانال در 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:
نمایش بیشتر📈 تحلیل کانال تلگرام Artificial Intelligence && Deep Learning
کانال Artificial Intelligence && Deep Learning (@deeplearning_ai) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 58 024 مشترک است و جایگاه 2 297 را در دسته فناوری و برنامهها و رتبه 6 023 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 58 024 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 23 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -218 و در ۲۴ ساعت گذشته برابر -10 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 8.90% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً N/A% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 5 163 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 15 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند github, learning, estimation, dataset, engineer تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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:”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 24 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
58 024
مشترکین
-1024 ساعت
-557 روز
-21830 روز
آرشیو پست ها
This channels is for Programmers, Coders, Software Engineers.
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StreamDiffusion: A Pipeline-level Solution for Real-time Interactive Generation
paper: https://arxiv.org/pdf/2312.12491v1.pdf
source code: https://github.com/cumulo-autumn/streamdiffusion?tab=readme-ov-file
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Generative Models by Stability AI
source code: https://github.com/stability-ai/generative-models
paper: https://static1.squarespace.com/static/6213c340453c3f502425776e/t/655ce779b9d47d342a93c890/1700587395994/stable_video_diffusion.pdf
provided a streamlit demo for text-to-image and image-to-image sampling in scripts/demo/sampling.py. They provide file hashes for the complete file as well as for only the saved tensors in the file ( see Model Spec for a script to evaluate that).
This channels is for Programmers, Coders, Software Engineers.
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* PIPNet's precision in facial landmark detection with a record 2.6% NME on the 300W benchmark. Explore the model and its capabilities by visiting our GitHub repository.
Watch the performance showcase on YouTube. Support and star our project on GitHub for future advancements.
video: https://www.youtube.com/watch?v=cxi1WQr-HKE
source code: https://github.com/Shohruh72/PIPNet/tree/main
join our community:
👉 @deeplearning_ai
PIPNet Facial Landmark Detection
PIPNet model has achieved a significant milestone on the 300W dataset, one of the most challenging benchmarks in facial landmark detection. Successfully attained a minimum Normalized Mean Error (NME) of 2.6%, demonstrating the model's high accuracy and robustness in complex facial recognition tasks.
video: https://www.youtube.com/watch?v=cxi1WQr-HKE
source code: https://github.com/Shohruh72/PIPNet/tree/main
+1VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
🤗🤗🤗 VideoCrafter is an open-source video generation and editing toolbox for crafting video content.
It currently includes the Text2Video and Image2Video models:
https://github.com/ailab-cvc/videocrafter
This channels is for Programmers, Coders, Software Engineers.
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Harvard CS50 – Free Computer Science Course (2023 Edition)
Here are the lectures included in this course:
Lecture 0 - Scratch
Lecture 1 - C
Lecture 2 - Arrays
Lecture 3 - Algorithms
Lecture 4 - Memory
Lecture 5 - Data Structures
Lecture 6 - Python
Lecture 7 - SQL
Lecture 8 - HTML, CSS, JavaScript
Lecture 9 - Flask
Lecture 10 - Emoji
Cybersecurity
https://www.freecodecamp.org/news/harvard-university-cs50-computer-science-course-2023/
join our community:
👉 @deeplearning_ai
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