⚡️ Graph Machine Learning

Free advanced course: Machine learning on graphs .

The course is regularly supplemented with practical problems and slides. The author Xavier Bresson is a professor at the National University of Singapore.

▪ Introduction

▪ Dive into graphs
- Lab1: Generate LFR social networks
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code01.ipynb

- Lab2: Visualize spectrum of point cloud & grid
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code02.ipynb

- Lab3/4: Graph construction for two-moon & text documents
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code03.ipynb

https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code04.ipynb

▪ Graph clustering
- Lab1: k-means
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code01.ipynb

https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code02.ipynb

- Lab2: Metis
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code03.ipynb

- Lab3/4: NCut/PCut
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code04.ipynb

https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code05.ipynb

- Lab5: Louvain
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code06.ipynb
https://pic.twitter.com/vSXCx364pe

▪ Lectures 4 Graph SVM
- Lab1 : Standard/Linear SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code01.ipynb

- Lab2 : Soft-Margin SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code02.ipynb

- Lab3 : Kernel/Non-Linear SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code03.ipynb

- Lab4 : Graph SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code04.ipynb

Running instructions: https://storage.googleapis.com/xavierbresson/lectures/CS6208/running_notebooks.pdf

💡 Github

✅ https://news.1rj.ru/str/DataScienceT

🦙 Fintuning Llama 3 using ORPO.

A quick guide on how to set up your new Llama 3 8B with ORPO .

I hope you will enjoy!

🤗 Model : https://huggingface.co/mlabonne/OrpoLlama-3-8B

💻 Colab : https://colab.research.google.com/drive/1eHNWg9gnaXErdAa8_mcvjMupbSS6rDvi?usp=sharing

📝 Article : https://huggingface.co/blog/mlabonne/orpo-llama-3

✅ https://news.1rj.ru/str/DataScienceT

🦾 🦏 Power of matplotlib

This beauty can be made using matplotlib . This is a visualization of an engraving by the German artist Albrecht Dürer, depicting an Indian rhinoceros, as the artist imagined it from the denoscriptions and drawings available to him in 1515.

Want to learn the same thing: here's a cool free book: " Scientific Visualization: Python + Matplotlib "

The sources of the book with code examples are here .

▪ Poster
▪ Book
▪ Code from the book

✅ https://news.1rj.ru/str/DataScienceT

🛞 6Img-to-3D driving scenarios 🛞

👮‍♀️ EPFL (+ Continental) unveils 6Img-to-3D, novel transformer-based encoder-renderer method to create 3D onbounded outdoor driving scenarios with only six pics

🥺 Review: https://shorturl.at/dZ018

🤨 Paper: arxiv.org/pdf/2404.12378.pdf

👉 Project: 6img-to-3d.github.io/

👉 Code: github.com/continental/6Img-to-3D

✅ https://news.1rj.ru/str/DataScienceT

📁 Machine Learning and Health Science Research: Tutorial

📕 Journal: Journal of Medical Internet Research (I.F.= 7.4)
🗓 Publish year: 2024

📱 Authors: Hunyong Cho, Jane She, Daniel De Marchi, ...
🏢 University: University of North Carolina at Chapel Hill, United States

📎 Study the paper

🗣 OpenVoice V2 - a Text-to-Speech model that can clone any voice and speak in any language.

OpenVoice V2 is a new version of the open text-to-speech model that allows you to clone any voice and generate speech in various languages.

• Github: https://github.com/myshell-ai/OpenVoice/tree/main
• Usage: https://github.com/myshell-ai/OpenVoice/blob/main/docs/USAGE.md