Machine Learning Issue #02

Topological graph neural networks, why machine learning algorithms are hard to tune & technical challenges for Training Fair Neural Networks & more.

Hey guys and gals, couple of announcements to make,

I am launching a new machine learning book. I am currently in the process of writing a book for understanding fundamental machine learning algorithms from scratch, I assume the reader has no knowledge of machine learning or just trying to start. This book will offer a variety of machine learning algorithms from scratch implementations and the mathematics behind them. The book is in the early stages and will be distributed for free over the internet. You can get early access to this put just filling up this contact form here,

And the next is the new machine learning issue 02. This week of machine learning issue we have topological graph neural networks, why machine learning algorithms are hard to tune, technical challenges for Training Fair Neural Networks, A language learning system that pays attention — more efficiently than ever before from MIT Research, Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals, and a new tool EasyNMT - Easy to use, state-of-the-art Neural Machine Translation, & Physics-informed neural networks with hard constraints for the inverse design.

Here is the link to the post Machine Learning Issue #02

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