Snap http://snap.stanford.edu/snappy/index.html, this library is also good and lot of work has been and best part is this runs in parallel mode.
Some Lesser Known Machine Learning Libraries
31–40 of 54 posts
Re: Some Lesser Known Machine Learning Libraries
#32Another fantastic library for the list - GRT https://github.com/nickgillian/grt
Really great lightweight c++ gesture recognition with DTW, HMM's and SVM's
Re: Some Lesser Known Machine Learning Libraries
#33What about mlpy, shark, mlpack, shogun, orange, elki, HLearn, etc.? There is very much the list doesn't cover (no offense to the list authors---just, there is a lot out there).
Re: Some Lesser Known Machine Learning Libraries
#34If I was going to try machine learning I would code up from scratch rather than relying on black boxes.
These algorithms usually are not black boxes with respect to their mathematical content. And the code is usually open source, so you are free to audit them for your arrogant self.
The term "black box" is used to refer to the fact that it's not always clear how to interpret a model like a deep neural network. It's a statistical issue, not a software issue.
Re: Some Lesser Known Machine Learning Libraries
#35Re: Some Lesser Known Machine Learning Libraries
#36Earlier quoted context omitted.
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…
You need to have some demos that one can download and get to work easily. Before you say "we do - look at this link..." see sentence 1.
https://deeplearning4j.org/quickstart
I agree with you if my aim were to mainly promote new users here - I was more targeting someone who knew what dl4j was already and had maybe used it.
I usually don't comment unless someone mentions the library by name. 99.99999% of the people who comment on here are going to likely be more interested in python in which I usually point them at keras.
Thanks for the feedback though! I'm not sure what to do beyond "git clone and import into intellij".
If you'd like feel free to file an issue on I'm guessing? the nd4j repo you were looking at? We always take feedback seriously if people take 5 seconds to post problems they've found. My head of training does our docs and videos and updates the site when he can.
Here are some of our youtube videos: https://www.youtube.com/channel/UCa-HKBJwkfzs4AgZtdUuBXQ
Re: Some Lesser Known Machine Learning Libraries
#37What about mlpy, shark, mlpack, shogun, orange, elki, HLearn, etc.? There is very much the list doesn't cover (no offense to the list authors---just, there is a lot out there).
Also probabilistic programming stuff: PyMC, Stan, Dimple, Church. Not sure if these are 'lesser known', PyMC is mentioned often, still much less hype nowadays than neural networks.
Re: Some Lesser Known Machine Learning Libraries
#38Re: Some Lesser Known Machine Learning Libraries
#39Pymanopt is a Python version of the Matlab code Manopt by Nicolas Boumal. It adds some features like automatic differentiation. I can't speak highly enough about both of these packages. A lot of people don't realize how useful manifold optimization is. The academic community has been aware of it for a while now, but it seems to have remained a bit of a secret.
It can be used to perform SVD, phase retrieval, global registration of point clouds, and low rank modeling.
I'm (very slowly) writing a Julia port of the code, so if someone wants to take over, feel free.
Re: Some Lesser Known Machine Learning Libraries
#40What about mlpy, shark, mlpack, shogun, orange, elki, HLearn, etc.? There is very much the list doesn't cover (no offense to the list authors---just, there is a lot out there).
Also probabilistic programming stuff: PyMC, Stan, Dimple, Church. Not sure if these are 'lesser known', PyMC is mentioned often, still much less hype nowadays than neural networks.
Thanks for the suggestions. I don't think PyMC3 and Stan are less known, hence did not suggest to add them in the list.
Dimple and Church look good additions. Will get them appended.