Gorgonia VS XcodeBenchmark

GitHub - gorgonia/gorgonia: Gorgonia is a library that helps facilitate machine learning in Go.

I did end up writing and using a custom library for Random Forest (it's also in AwesomGo) in one real-world project (detecting Alzheimer's and Parkinson's from speech from a mobile app) - https://github.com/malaschitz/randomForest I had better results than the team who used TensorFlow and most importantly I didn't have to use any other technology than Go. For NN's it's probably best to use https://gorgonia.org/ - but it's not exactly a user friendly library. But there is a whole book on it - Hands-On Deep Learning with Go.

Perhaps it's a product of French culture, but because Gorgonia[0] has a number of French contributors, this was actually the way we structured our documentation.

But this is the first time I've heard of the name of the framework.

[0]: https://gorgonia.org

Oh it's.Gorgonia

Website: https://gorgonia.org

I use Gorgonia.

What you think about this https://github.com/gorgonia/gorgonia ? I also recall there is something else out there but can't find it at the moment...

Yep, all of them: https://github.com/gorgonia/gorgonia

I’m a software developer as well and I ended up ordering a m3 max (still not received though). Main reasons against the m3 pro was the lesser number of performance cores compared to previous gens and slower memory bandwidth. Indeed, in this Xcode benchmark used by the Max Tech channel, the m3 pro compiled code slightly slower than the M1 Pro. Probably is a corner case but I think it’s worth to mention.

I found only one reasonable benchmark comparing compilation speed for large projects here. Does anyone have experience with these 2 machines for backend development with compiled languages?

Here's repo you should look at when buying a MacBook. Difference between M2 Pro and M2 Max is ~15%.

I'm not sure about AI/ML dataset training performance, but this XcodeBenchmark performance appears to be very comparable between the M2 and M2 Pro.