Hello Sirs, Good Day! I am planning on applying for "Example zoo" for this GSoC.
As I am machine learning practitioner, it will be very interesting and helpful for me in the same way to implement various machine learning algorithms and see how they perform. So it will be very helpful if you can advice me a little on how this project direction should go[ I don't want to deviate from the vision of this project]. Let me breakdown what I understand: 1. Implementing ML models on different datasets in form of jupyter notebook or code, in short a sort of tutorial to showcase our library and its usage. 2. Having code snippets which we can add in documentation/blog of those algorithms, so that newcomer has an easy idea on how to use it or just copy the code and use it in their project. 3.Having interesting pictures or diagrams explaining the algorithm. 4. Visualization of metrics and losses. @Ryan Curtin @zoq I read the future of mlpack and I think there was mention about this project as one of key part. I think I can contribute a part here, so it will be very helpful if you can guide me how this should go. This will be my first GSoC and it will be very helpful to get a word of mouth. P.S.: I read the details on the project on GSoC page of our organization, but still wanted to discuss in depth on this project. Regards Roshan Swain @swaingotnochill
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