Computer Science and Programming
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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:
Ko'proq ko'rsatishπ Telegram kanali Computer Science and Programming analitikasi
Computer Science and Programming (@machinelearning_programming) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 14 299 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 8 921-o'rinni va Hindiston mintaqasida 27 774-o'rinni egallagan.
π Auditoriya koβrsatkichlari va dinamika
Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ sanasidan buyon loyiha tez oβsib, 14 299 obunachiga ega boβldi.
25 Oktabr, 2026 dagi oxirgi maβlumotlarga koβra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -95 ga, soβnggi 24 soatda esa -2 ga oβzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oβrtacha 0% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni toβplaydi.
- Post qamrovi: Har bir post oβrtacha 0 marta koβriladi; birinchi sutkada odatda 0 ta koβrish yigβiladi.
- Reaksiyalar va oβzaro taβsir: Auditoriya faol: har bir postga oβrtacha 0 ta reaksiya keladi.
- Tematik yoβnalishlar: Kontent learning, github, engineer, quantization, detection kabi asosiy mavzularga jamlangan.
π Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taβriflaydi:
βChannel 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:β
Yuqori yangilanish chastotasi (oxirgi maβlumot 26 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boβlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taβsir nuqtasiga aylantirishini koβrsatadi.
14 299
Obunachilar
-224 soatlar
-317 kun
-9530 kun
Postlar arxiv
π Aruco Pose Estimator: Elevate Your Vision Projects!
π― 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.
π½ Real-Time Visualization:
β¨ 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!
β
@MachineLearning_Programming
π Bring Your Portraits to Life with LivePortrait AI! π
π¨ Introducing LivePortrait: The Ultimate Tool for Animated Portraits π¨
π Features:
β¨ One-Click Animation: Generate animated portraits effortlessly.
π Keypoint Detection: Precise facial keypoint transformation.
π₯ Video Processing: Drive animations with video inputs.
π§ Model Integration: Seamlessly combines various advanced models.
π Template Creation: Create consistent and repeatable motion templates.
β¨ Why LivePortrait?
User-Friendly: Intuitive design for easy use.
High-Quality Animations: Realistic and captivating results.
π Check it out on GitHub:
LivePortrait AI GitHub Repository
#Watch_the_magic_happen_with_just_one_click!
βοΈ Give us a star and join the revolution in portrait animation! βοΈ
β
https://t.me/deeplearning_ai
π 3DGazeNet: Revolutionizing Gaze Estimation with Weak-Supervision! π
Key Features:
πΉ Advanced Neural Network: Built on the robust U2-Net architecture.
πΉ Comprehensive Utilities: Easy data loading, preprocessing, and augmentation.
πΉ 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.
π»Source Code: https://github.com/Shohruh72/3DGazeNet
πRead the Paper: Access Here
#3DGazeNet #GazeEstimation #AI #DeepLearning #TechInnovation
Join us in pushing the boundaries of gaze estimation technology with 3DGazeNet!π 3DGazeNet: Revolutionizing Gaze Estimation with Weak-Supervision! π
Key Features:
πΉ Advanced Neural Network: Built on the robust U2-Net architecture.
πΉ Comprehensive Utilities: Easy data loading, preprocessing, and augmentation.
πΉ 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.
π»Source Code: https://github.com/Shohruh72/3DGazeNet
πRead the Paper: Access Here
#3DGazeNet #GazeEstimation #AI #DeepLearning #TechInnovation
Join us in pushing the boundaries of gaze estimation technology with 3DGazeNet!πFace Identification Inference Code Using ONNX Runtimeπ
π’ Introducing AdaFace: Quality Adaptive Margin for Face Recognition
Hello tech enthusiasts! π
Our project leverages the power of ONNX Runtime to deliver high-accuracy face identification.
π Check out our project and see it in action!
π Visit our GitHub Repository: AdaFace on GitHub
We need your support to make this project even better! Hereβs how you can help:
βοΈ Star our repository to show your appreciation and help us gain more visibility.
π Share with your network to spread the word about AdaFace.
π Give us feedback by reviewing the code and suggesting improvements.
Thank you for being part of our journey. Let's create something amazing! π
#FaceRecognition #ONNX #AdaFace #GitHub #OpenSource #TechInnovation
Happy Learning! π
πΉ 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.
π Resources:
π₯ GitHub
π€ Demo
β
VideoLLaMA 2 Model
Explore the capabilities of VideoLLaMA 2 and revolutionize your video generation projects!
Hey everyone! π
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*! π§βπ»
Discover the innovative Artifacts feature in Claude 3.5 Sonnet and learn how it enhances the model's capabilities for various applications!
π Date: Saturday, June 29
β° Time: 11 AM IST
*Register now*: buildfastwithai.com/events/claude-35-sonnet-deep-dive
See you there! π
π 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
π Unlock ML deployment secrets on top clouds & open source.
π‘ Dive into data management insights.
π οΈ Harness the latest MLOps tools.
π₯ Real-time expert interaction.
π₯ Limited spots! Enroll now:
https://bit.ly/mlops-webinar
π Share with ML enthusiasts! #MLOps #AI #TechTraining
Ultralytics YOLOv8 for Smarter Parking Management Systems
π»Project Details: Discover More
Are you struggling with invoking functions, passing arguments, or handling return values in Large Language Models (LLMs)?
Whether youβre a seasoned developer or just starting your journey in Gen AI.
In this session, weβll 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:
π Date: 14th June, Friday
β° Time: 9 PM, IST
π Link : https://www.buildfastwithai.com/events/function-calling-with-llms
βπ₯π₯βοΈ BEST DATA SCIENCE CHANNELS ON TELEGRAM π
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:
π @MachineLearning_Programming
π Join Our Team as a Senior Data Researcher at Wunder Fund! π
π Location: Remote/Relocation to various countries
πΈ 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.
πΎWhat Youβll Do:
- Train models, test hypotheses, and achieve maximum model accuracy
- Work with top-tier programmers, mathematicians, and physicists
π€What You Will Need:
- Proficiency in Python and Mathematics
- Experience with Kaggle (Master/Grandmaster)
- Success in training transformers and LSTM
π Learn More & Apply
π Discover LiteHPE: Advanced Head Pose Estimation π
Features:
π οΈ Setup in Minutes:
π Top-Tier Performance:
β
Achieve low Mean Absolute Error rates
β
Models range from MobileOne_s0 to s4
β
Pretrained models ready for download
π π Star us on GitHub for the latest updates: LiteHPE on GitHub.
Boost your project's capabilities with LiteHPE β 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 Nowπ
https://bit.ly/mlops-masterclass
π₯ Limited Seats Available!
βοΈ 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.
