اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Computer Science and Programming
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 * Related Courses and Ebooks With advertising offers contact:
نمایش بیشتر📈 تحلیل کانال تلگرام Computer Science and Programming
کانال Computer Science and Programming (@machinelearning_programming) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 14 851 مشترک است و جایگاه 8 724 را در دسته فناوری و برنامهها و رتبه 29 599 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 14 851 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 03 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -150 و در ۲۴ ساعت گذشته برابر -3 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 14.63% 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 0 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 0 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, github, engineer, quantization, detection 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
* Related Courses and Ebooks
With advertising offers contact:”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 04 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.
14 851
مشترکین
-324 ساعت
-227 روز
-15030 روز
آرشیو پست ها
🚀 Aruco Pose Estimator: Elevate Your Vision Projects!
🎯 Why Aruco Pose Estimator?
Real-Time Detection: Seamlessly detect ArUco markers in live video feeds.
3D Pose Estimation: Accurately estimate the orientation and position of markers.
Comprehensive Metrics: Get real-time pitch, yaw, roll, and distance estimations.
Key Features:
Real-Time Detection: Detects ArUco markers instantly.
3D Pose Estimation: Provides precise orientation and position.
Orientation Metrics: Calculates and displays pitch, yaw, and roll.
Distance Measurement: Estimates marker distance from the camera.
📽 Real-Time Visualization:
✨ Join the Community!
Boost your computer vision projects with Aruco Pose Estimator.
Explore more on GitHub and don't forget to give us a star!
✅ @MachineLearning_Programming
🚀 Bring Your Portraits to Life with LivePortrait AI! 🚀
🎨 Introducing LivePortrait: The Ultimate Tool for Animated Portraits 🎨
🔍 Features:
✨ One-Click Animation: Generate animated portraits effortlessly.
🔍 Keypoint Detection: Precise facial keypoint transformation.
🎥 Video Processing: Drive animations with video inputs.
🔧 Model Integration: Seamlessly combines various advanced models.
📄 Template Creation: Create consistent and repeatable motion templates.
✨ Why LivePortrait?
User-Friendly: Intuitive design for easy use.
High-Quality Animations: Realistic and captivating results.
🔗 Check it out on GitHub:
LivePortrait AI GitHub Repository
#Watch_the_magic_happen_with_just_one_click!
⭐️ Give us a star and join the revolution in portrait animation! ⭐️
✅ https://t.me/deeplearning_ai
🚀 3DGazeNet: Revolutionizing Gaze Estimation with Weak-Supervision! 🌟
Key Features:
🔹 Advanced Neural Network: Built on the robust U2-Net architecture.
🔹 Comprehensive Utilities: Easy data loading, preprocessing, and augmentation.
🔹 Seamless Integration: Train, test, and visualize with simple commands.
Demo Visualization:Visualize the demo by configuring your video path in
main.py and showcasing the power of 3DGazeNet.
Pretrained Weights:Quick start with our pretrained weights stored in the weights folder.
💻Source Code: https://github.com/Shohruh72/3DGazeNet
📖Read the Paper: Access Here
#3DGazeNet #GazeEstimation #AI #DeepLearning #TechInnovation
Join us in pushing the boundaries of gaze estimation technology with 3DGazeNet!🚀 3DGazeNet: Revolutionizing Gaze Estimation with Weak-Supervision! 🌟
Key Features:
🔹 Advanced Neural Network: Built on the robust U2-Net architecture.
🔹 Comprehensive Utilities: Easy data loading, preprocessing, and augmentation.
🔹 Seamless Integration: Train, test, and visualize with simple commands.
Demo Visualization:Visualize the demo by configuring your video path in
main.py and showcasing the power of 3DGazeNet.
Pretrained Weights:Quick start with our pretrained weights stored in the weights folder.
💻Source Code: https://github.com/Shohruh72/3DGazeNet
📖Read the Paper: Access Here
#3DGazeNet #GazeEstimation #AI #DeepLearning #TechInnovation
Join us in pushing the boundaries of gaze estimation technology with 3DGazeNet!🌟Face Identification Inference Code Using ONNX Runtime🌟
📢 Introducing AdaFace: Quality Adaptive Margin for Face Recognition
Hello tech enthusiasts! 🚀
Our project leverages the power of ONNX Runtime to deliver high-accuracy face identification.
🎉 Check out our project and see it in action!
🔗 Visit our GitHub Repository: AdaFace on GitHub
We need your support to make this project even better! Here’s how you can help:
⭐️ Star our repository to show your appreciation and help us gain more visibility.
🔄 Share with your network to spread the word about AdaFace.
📝 Give us feedback by reviewing the code and suggesting improvements.
Thank you for being part of our journey. Let's create something amazing! 🌟
#FaceRecognition #ONNX #AdaFace #GitHub #OpenSource #TechInnovation
Happy Learning! 🌟
🕹 VideoLLaMA 2: Open-Source Video-LLMs for Video Generation
VideoLLaMA 2 is a cutting-edge set of open-source Video-LLMs designed for advanced video generation. Building on the successes of previous models, VideoLLaMA 2 introduces a specialized space-time convolution (STC) component, enabling it to effectively capture complex dynamics in video.
🔗 Resources:
🖥 GitHub
🤗 Demo
✅ VideoLLaMA 2 Model
Explore the capabilities of VideoLLaMA 2 and revolutionize your video generation projects!
Hey everyone! 👋
Remember the sneak peek of Claude 3.5 at the end of last week's masterclass? Well, get ready for more!
This weekend, we're diving deep into *Claude 3.5 Sonnet*! 🧑💻
Discover the innovative Artifacts feature in Claude 3.5 Sonnet and learn how it enhances the model's capabilities for various applications!
🗓 Date: Saturday, June 29
⏰ Time: 11 AM IST
*Register now*: buildfastwithai.com/events/claude-35-sonnet-deep-dive
See you there! 🚀
🚀 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
Ultralytics YOLOv8 for Smarter Parking Management Systems
💻Project Details: Discover More
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
3D Shot Posture Dataset
This dataset consists of the 3d and 2d postures of professional football players under shot situations.
Content of the dataset:
In 3dsp/train
20 cropped image x 200 shot
Tracklet, 2d and 3d keypoints
In 3dsp/test
20 cropped image x 10 shots
Tracklet
https://github.com/calvinyeungck/3D-Shot-Posture-Dataset
join our community:
👉 @MachineLearning_Programming
🌟 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
🚀 Discover LiteHPE: Advanced Head Pose Estimation 🚀
Features:
🛠️ Setup in Minutes:
📈 Top-Tier Performance:
✅ Achieve low Mean Absolute Error rates
✅ Models range from MobileOne_s0 to s4
✅ Pretrained models ready for download
🌟 🌟 Star us on GitHub for the latest updates: LiteHPE on GitHub.
Boost your project's capabilities with LiteHPE – the forefront of head pose estimation technology!
#AI #MachineLearning #HeadPoseEstimation #Technology #DeepLearning
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.
