Computer Science and Programming

🌟FACE ID: Face Identification 🌟


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: FACE ID

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 Face ID.
📝 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! 🌟

🔗 GitHub_Link

❇️ MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

#Mesh

Join my channel: @MachineLearning_Programming

🚀 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.
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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

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

🔗 Join now: @MachineLearning_Programming

Learn to deploy Gen Ai Models to production 👇

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.

🚀 Explore AI News with Us! 🤖

Looking for top-notch AI updates?
Don't miss out on our Telegram channel!
We offer daily insights into the latest advancements, research papers, and industry news.

🔗 Join now: https://t.me/Artificial_Intelligence_Updates

Join our community of AI enthusiasts and stay ahead of the curve! 🌐✨

AiOS: The Future of Human Shape & Pose Recovery

Discover AiOS, the cutting-edge, unified framework by SenseTime, HKU, IDEA, S-Lab, and Shanghai AI Lab. AiOS redefines state-of-the-art expressive pose and shape recovery, seamlessly integrating advanced features without the need for separate human detection steps.

Highlights:

✅First-of-its-Kind: Single-stage EHPS with zero extra detection networks.
✅Innovative Design: Unique "Human-as-Tokens" concept for deeper insights.
✅Enhanced Dynamics: Sophisticated attention to human relationships.
✅Comprehensive Analysis: Unified feature system for unparalleled whole-body understanding.
✅Unmatched Performance: Top-tier results sans ground truth bounding boxes.

Explore More:
Project Page
Read the Paper

@MachineLearning_Programming

This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://t.me/addlist/8_rRW2scgfRhOTc0

✅ https://t.me/DataScienceM

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📢 FREE TRAINING:
Navigating the Landscape of MLOps & LLMOps 🚀

🔥 Join our FREE MLOps course demo and acquire essential skills for AI and data science across Multicloud 🚀

👉 Reserve your seat now:
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🌟 What you'll gain:
1️⃣ ML model deployment techniques on AWS, Azure, GCP & open source.
2️⃣ Efficient data management insights.
3️⃣ Explore the latest MLOps tools.
4️⃣ Real-time interaction with expert instructors.

🚩 Limited spots available! Don't miss out!

👉 Enroll now:
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👥 Share with fellow ML enthusiasts! 🚀✨

🌟 Discover 6DRepNet: The Ultimate Head Pose Estimation Model!

Features:
* State-of-the-art accuracy
* Comprehensive tools for training, testing, and inference
* Easy setup with conda
* Supports multiple datasets

Watch the performance showcase on GitHub for future advancements.

[Source Code] [Paper]

join our community:
👉 @deeplearning_ai