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ageron / handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Apache License 2.0
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[IDEA] Requesting to Include Graph Neural Networks #34

Open Kirushikesh opened 1 year ago

Kirushikesh commented 1 year ago

The field of graph representation learning has grown at an incredible and sometimes unwieldy pace over the past few years, and a lot of new algorithms and innovations were made in the field. I read the second version completely it's a power-packed guide for beginners to gain knowledge on both machine learning and deep learning. But I find this important puzzle was missing there, I request the author to add a chapter on graph neural networks in upcoming versions. The hands-on experience with graph neural networks will be useful for all the readers. Thanks.

ageron commented 1 year ago

Hi @Kirushikesh , Thanks for your kind words and your suggestion. I agree with you, I'm also really excited by the progress made in GNNs, and I actually considered introducing GNNs in the 3rd edition, but I already had quite a few things to add, so unfortunately, GNNs didn't make it in. I'll definitely try to add them to the next edition. 👍

ageron commented 1 year ago

Btw, I enjoyed this great introduction to GNNs by Petar Veličković. It's a good starting point for anyone wanting to dip their toes in this exciting field.

Please feel free to point to other nice introductory resources in the comments below for anyone who might stumble upon this thread.

lucaswerner90 commented 1 year ago

+1 this request!

First of all, thanks @ageron for the amazing content on the 3rd edition! I'm really enjoying the updates from the 2nd edition!

There's a book called "Graph-Powered Machine Learning" by Alessandro Negro which seems to be one of the few resources available out there about the topic.