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Please don't spread bad advice. There is a reason we teach Python and not ia64 Assembly to beginners.
> There is a reason we teach Python and not ia64 Assembly to beginners. Fashion is a reason, but it's not a good reason.
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"Less known libraries" would be libraries that fewer people know. "Lesser known libraries" would be libraries of a lower quality.
[source](http://english.stackexchange.com/questions/24719/difference-...)
If I was going to try machine learning I would code up from scratch rather than relying on black boxes.
Maybe the libraries are less known because they're lesser libraries? --- "Less known libraries" would be libraries that fewer people know. "Lesser known libraries" would be libraries of a lower quality. [source]( http://english.stackexchange.com/questions/24719/difference-... )
If I was going to try machine learning I would code up from scratch rather than relying on black boxes.
As someone who actually did this, got in to YC, raised a few million and built a team of 22 distributed across 6 timezones around said endeavor: Don't. It's been 3.5 years since I did it and I don't regret it necessarily but the only reason I did was because I wanted something in an unserved category.
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scikit-learn is a production ready library that has some very well commented and easy to read source code. https://github.com/eriklindernoren/ML-From-Scratch is an easy to understand understand implementation of some the basic ML algorithms built from first principles and aims for readability over performance.
I was asking about the ones which don't have very good documentation and are in need of contributors.
Earlier quoted context omitted.
Please don't spread bad advice. There is a reason we teach Python and not ia64 Assembly to beginners.
> There is a reason we teach Python and not ia64 Assembly to beginners. Fashion is a reason, but it's not a good reason.
Earlier quoted context omitted.
I feel at this point this is not a sensible thing to do any more unfortunately. I totally get the impulse though. For instance, there is still nothing great on the JVM for deep learning with symbolic differentiation (deeplearning4j does not have this, correct me if this has changed). On the other hand, I realize that between writing native interfaces, symbolic differentiation (e.g. writing a port of autograd), networ…
We are adding this now to our tensor library: https://github.com/deeplearning4j/nd4j/pull/1750 I've also added numpy interop via our new python interface jumpy: https://github.com/deeplearning4j/jumpy We are doing a lot more than autograd though, this is going to support dynamic computation graphs, give you direct access to a graph data structure and will later be usable from nd4s (our scala wrapper) Rather than spen…
Maybe the libraries are less known because they're lesser libraries? --- "Less known libraries" would be libraries that fewer people know. "Lesser known libraries" would be libraries of a lower quality. [source]( http://english.stackexchange.com/questions/24719/difference-... )