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< abhinav_> hello
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< abhinav_> hi
< zoq> abhinav_: Hello there
< abhinav_> I wanted to contribute to mlpack
< abhinav_> Any suggestions, How to get started ?
< abhinav_> I have read the tutorials
< zoq> So I guess it might be a good idea to look into the open issues on github.
< abhinav_> Which issue would be a good one to target
< zoq> There are a few issues on Github that might be a good place to jump in. We tag them by difficulty, so here are the "easy" tickets:
< zoq> If you tell us more about you're interests we might probably be able to add some more issues in that direction.
< abhinav_> I am quite interested in ML and AI algorithms. I have used some of the libraries available and completed a few online courses
< abhinav_> Now I wanted to start contributing to the libraries so that I can implement the algorithms I have been using
< abhinav_> I can share my cv if u want
< zoq> If you have implemented any new algorithms in your previous work we are happy to merge them in. The algorithm has to be tested and should follow the design guidelines.
< zoq> So, maybe we can find a concrete method/algorithm you like to contribute.
< abhinav_> No i haven't implemented any new algorithms
< abhinav_> I have used the algorithms to develop applications until now
< zoq> There are also some ideas on the GSoC ideas page, that might be interesting: https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas
< abhinav_> So what would be better
< abhinav_> To start with issues or try my hands on with the ideas
< abhinav_> ?
< zoq> The issues are more like mini projects and the GSoC ideas are projects that take some time.
< abhinav_> ok
< abhinav_> I think I'll try the issues first
< abhinav_> Thanks
< zoq> You are welcome, let us know if we can help you with anything.
< abhinav_> yeah sure
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< travis-ci> mlpack/mlpack#1612 (master - 8c91b01 : Ryan Curtin): The build passed.
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