Вже доступно! Дослідження Telegram за 2025 — головні інсайти року 
Artificial Intelligence && Deep Learning
Відкрити в 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:
Показати більше📈 Аналітичний огляд Telegram-каналу Artificial Intelligence && Deep Learning
Канал Artificial Intelligence && Deep Learning (@deeplearning_ai) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 57 992 підписників, посідаючи 2 291 місце в категорії Технології та додатки та 5 956 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 57 992 підписників.
За останніми даними від 29 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -192, а за останні 24 години на -20, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 10.78%. Протягом перших 24 годин після публікації контент зазвичай збирає N/A% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 0 переглядів. Протягом першої доби публікація в середньому набирає 0 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 0.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як github, learning, estimation, dataset, engineer.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“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:”
Завдяки високій частоті оновлень (останні дані отримано 30 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Технології та додатки.
57 992
Підписники
-2024 години
-267 днів
-19230 день
Архів дописів
🚀 MLOps Market to reach US$4 Billion in 2025
Unleash MLOps Mastery - FREE Training on AWS, Azure, GCP & Open-source!
Navigating the Landscape of MLOps & LLMOps
🌟 Unlock ML deployment secrets on top clouds & open source.
💡 Dive into data management insights.
🛠️ Harness the latest MLOps tools.
👥 Real-time expert interaction.
🔥 Limited spots! Enroll now:
https://bit.ly/mlops-webinar
🚀 Share with ML enthusiasts! #MLOps #AI #TechTraining
Grounding DINO 1.5
IDEA Research's Most Capable Open-World Object Detection Model Series.
Explore More:
💻Source Code: Explore on GitHub
💻Try DEMO: Discover More
📖Read the Paper: Access Here
Depth Anything2: Unleashing the Power of Large-Scale Unlabeled Data
This work presents Depth Anything, a highly practical solution for robust monocular depth estimation by training on a combination of 1.5M labeled images and 62M+ unlabeled images.
Explore More:
💻Source Code: Explore on GitHub💻Project Details: Discover More
📖Read the Paper: Access Here
Are you struggling with invoking functions, passing arguments, or handling return values in Large Language Models (LLMs)?
Whether you’re a seasoned developer or just starting your journey in Gen AI.
In this session, we’ll explore the fascinating world of invoking functions using LLMs.
1. Introduction to LLMs.
2. Function Calls: Basics and Syntax.
3. Live Coding Examples.
4. Q&A Session.
Register For Free:
🗓 Date: 14th June, Friday
⏰ Time: 9 PM, IST
🔗 Link : https://www.buildfastwithai.com/events/function-calling-with-llms
Are you struggling with invoking functions, passing arguments, or handling return values in Large Language Models (LLMs)?
Whether you’re a seasoned developer or just starting your journey in Gen AI.
In this session, we’ll explore the fascinating world of invoking functions using LLMs.
1. Introduction to LLMs.
2. Function Calls: Basics and Syntax.
3. Live Coding Examples.
4. Q&A Session.
Register For Free:
🗓 Date: 14th June, Friday
⏰ Time: 9 PM, IST
🔗 Link : https://www.buildfastwithai.com/events/function-calling-with-llms
⭐🔥💥☄️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 👇
https://t.me/addlist/8_rRW2scgfRhOTc0
🌟 Join Our Team as a Senior Data Researcher at Wunder Fund! 🌟
🚀 Location: Remote/Relocation to various countries
💸 Salary: $5k-$7k+ per month (USD or Crypto)
At wunderfund.io we've been in the HFT trading game since 2014 and our daily trading volume is around $8B. We're looking for a Senior Data Researcher to lead our neural networks direction.
👾What You’ll Do:
- Train models, test hypotheses, and achieve maximum model accuracy
- Work with top-tier programmers, mathematicians, and physicists
🤓What You Will Need:
- Proficiency in Python and Mathematics
- Experience with Kaggle (Master/Grandmaster)
- Success in training transformers and LSTM
🌐 Learn More & Apply
🚀 Introducing Emotion Recognition with ONNX Runtime!
Transform your projects with real-time face detection and emotion recognition. Dive into our latest repo and see the magic unfold!
🌟 Key Features:
* Real-time face detection with ONNX models.
* Accurate emotion recognition from detected faces.
* Live visualization of emotion scores.
⭐️ Star our repo and elevate your AI projects: Emotion Recognition on GitHub
Join us on this exciting journey and let’s push the boundaries of AI together! 🚀👩💻👨💻
FREE Machine Learning & Artificial Intelligence Certified Courses
👇👇
https://t.me/machinelearning_deeplearning
Amazing premium resources only for my subscribers
🎁 Free Data Science Books
🎁 Machine Learning Handwritten Notes
🎁 Python Free Learning Resources
🎁 Learn AI with ChatGPT
🎁 Build Chatbots using LLM
🎁 Learn Generative AI
🎁 Free Coding Certified Courses
Free Access to our paid data science community today:
👇👇
https://t.me/+rpxYNC0LbFc0YWEx
Hope you like it 😀
🔍 Discover the Power of Fine-Grained Gaze Estimation with L2CS-Net! 🌟
🚀 Key Features:
✅Advanced Architecture: Built using state-of-the-art neural network structures.
✅Versatile Utilities: Packed with utility functions and classes for seamless integration.
✅Robust Data Handling: Efficient data loading, preprocessing, and augmentation.
✅Comprehensive Training & Testing: Easy-to-follow scripts for training and testing your models.
👀 Live Demo:
Visualize the power of L2CS-Net with your own video:
🌟 Join Us:
Star our repo on GitHub and be part of the innovative community pushing the boundaries of gaze estimation. Your support drives us forward!
🔗 GitHub Repository
Let's advance gaze estimation together! 🚀🌐 #GazeEstimation #DeepLearning #AI #MachineLearning #ComputerVision
🚀 Explore SCRFD: High-Efficiency, High-Accuracy Face Detection 🚀
Unlock next-level face detection capabilities with SCRFD – efficiency and accuracy in one solution!
📈 Performance at a Glance:
✅Model range: SCRFD_500M to SCRFD_34G
✅Accuracy up to 96.06%
✅Inference as fast as 3.6 ms
🔍 Explore more and consider starring our repo for updates:
--- GitHub Repository.
--- Paper
#AI #MachineLearning #FaceDetection #TechInnovation #DeepLearning
✅ https://t.me/deeplearning_ai
MLOps Masterclass
Productionizing Generative AI models, Navigating the Landscape of MLOps & LLMOps - Understanding the Synergy
Schedule:
May 25th (Sat) & 26th (Sun), 10AM to 3:30 PM
Register Now👇
https://bit.ly/mlops-masterclass
🔥 Limited Seats Available!
☎️ Contact:
Sarath Kumar
+918940876397 / +918778033930
India's Largest Free Webinar on LLMs especially focused on the recently released LLAMA-3 by Meta.
How do you use these models?
How can you create apps with them?
Join our free workshop on to learn how to use Llama 3 and create apps with it.
Register here: https://www.buildfastwithai.com/events/llama-3-deep-dive
You can connect with Founder;
https://www.linkedin.com/in/satvik-paramkusham/
This Event is especially designed for people interested in the field of AI, ML, GenAI & LLMs.
🔍 Introducing UniRef++: Advanced Object Segmentation in Spatial and Temporal Domains
🚀 Key Features:
Unified Model: UniRef++ seamlessly handles segmentation tasks:
✅Referring Image Segmentation (RIS)
✅Few-Shot Segmentation (FSS)
✅Referring Video Object Segmentation (RVOS)
✅Video Object Segmentation (VOS)
Core Component: UniFusion module
✅Integrates reference information efficiently
✅Utilizes flash attention for high efficiency
Compatibility: Acts as a plug-in for foundational models like SAM
🌐 UniRef++ is the official extended implementation from ICCV 2023's UniRef.
Stay tuned for more updates!
👉 Code: https://github.com/FoundationVision/UniRef
🤨 Paper: [Paper link]
✅ https://t.me/deeplearning_ai
Neural Bodies with Clothes: Overview
Introduction: Neural-ABC, a cutting-edge parametric model developed by the University of Science & Technology of China, innovatively represents clothed human bodies.
Key Features:
✅Novel approach for modeling clothed human figures.
✅Unified framework accommodating various clothing types.
✅Consistent representation of both body and clothing.
✅Enables seamless modification of identity, shape, clothing, and pose.
✅Extensive dataset with detailed clothing information.
Explore More:
💻Project Details: Discover More
📖Read the Paper: Access Here
💻Source Code: Explore on GitHub
Relevance: #artificialintelligence #machinelearning #AI #deeplearning #computervision #AIwithPapers #metaverse
join our community:
👉 @deeplearning_ai
🕷️🕷️ GenN2N: Generative NeRF2NeRF Translation.🕷️🕷️
Key Features:
* Collaborative Excellence.
* Advanced 3D VAE-GAN Architecture
* Universal NeRF Editing
* Contrastive Learning
* Optimized Performance
[Paper]
[Source Code]
[Project Page]
Join our community: @deeplearning_ai
Introducing ECoDepth: The New Benchmark in Diffusive Mono-Depth
From the labs of IITD, we unveil ECoDepth - our groundbreaking SIDE model powered by a diffusion backbone and enriched with ViT embeddings. This innovation sets a new standard in single image depth estimation (SIDE), offering unprecedented accuracy and semantic understanding.
Key Features:
✅Revolutionary MDE approach tailored for SIDE tasks
✅Enhanced semantic context via ViT embeddings
✅Superior performance in zero-shot transfer tasks
✅Surpasses previous SOTA models by up to 14%
Dive into the future of depth estimation with ECoDepth. Access our source code and explore the full potential of our model.
📖 Read the Paper
💻 Get the Code
#ArtificialIntelligence #MachineLearning #DeepLearning #ComputerVision #AIwithPapers #Metaverse
join our community:
👉 @deeplearning_ai
