Endi mavjud! Telegram Tadqiqoti 2025 — yilning asosiy insaytlari 
Artificial Intelligence && Deep Learning
Kanalga Telegram’da o‘tish
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:
Ko'proq ko'rsatish📈 Telegram kanali Artificial Intelligence && Deep Learning analitikasi
Artificial Intelligence && Deep Learning (@deeplearning_ai) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 58 024 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 297-o'rinni va Hindiston mintaqasida 6 023-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 58 024 obunachiga ega bo‘ldi.
23 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -218 ga, so‘nggi 24 soatda esa -10 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 8.90% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 5 163 marta ko‘riladi; birinchi sutkada odatda 0 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 15 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent github, learning, estimation, dataset, engineer kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“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:”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 24 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
58 024
Obunachilar
-1024 soatlar
-557 kunlar
-21830 kunlar
Postlar arxiv
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ best channels on Telegram:
https://t.me/addlist/8_rRW2scgfRhOTc0
✅ Data Science Books:
https://t.me/DataScienceM
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.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
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8- programming Languages
✅ best channels on Telegram:
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✅ Data Science Books:
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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.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ best channels on Telegram:
https://t.me/addlist/8_rRW2scgfRhOTc0
✅ Data Science Books:
https://t.me/DataScienceM
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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MLOps Masterclass
🔥50% OFF on registration
🏆 Unlock your full potential with MLOps Masterclass
Learn to Design ML Pipelines to Build, Train,Deploy and Monitor your ML models in a real-time production environment.
Register Now👇
https://bit.ly/mlops-nov23
Why you shouldn't miss this Masterclass?
✔️ 15+ hands-on exercises.
✔️ 2 Real-life industry projects.
✔️Dedicated mentoring sessions from industry experts.
✔️ 10 hours session consisting of theory + Hands-on.
✔️One-on-One Debugging Session (Optional)
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November 18th (Sat) & 19th (Sun)
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▪️MLOps Introduction
▪️Getting started with AWS for Machine Learning
▪️AWS SageMaker Studio
▪️CI/CD Tools
▪️AWS MLOps Tools
▪️AWS MLOps - Build, Train & deploy ML Model
🔥 Limited Seats Available!
☎️ Contact:
Sarath Kumar
+918940876397 / +918778033930
