Available now! Telegram Research 2025 β the year's key insights 
Computer Science and Programming
Open in 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:
Show moreπ Analytical overview of Telegram channel Computer Science and Programming
Channel Computer Science and Programming (@machinelearning_programming) in the English language segment is an active participant. Currently, the community unites 14 843 subscribers, ranking 8 736 in the Technologies & Applications category and 29 532 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 14 843 subscribers.
According to the latest data from 04 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -152 over the last 30 days and by -7 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 14.63%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
- Post reach: On average, each post receives 0 views. Within the first day, a publication typically gains 0 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
- Thematic interests: Content is focused on key topics such as learning, github, engineer, quantization, detection.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
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
Thanks to the high frequency of updates (latest data received on 05 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
14 843
Subscribers
-724 hours
-277 days
-15230 days
Posts Archive
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.
