[mlpack] Proposing a possible project for GSOC 2021

[Nippun Sharma]

Hi everyone,

Here I will be proposing a possible project for GSOC 2021.
This project is inspired by #2421
<https://github.com/mlpack/mlpack/issues/2421>.

Majority of the machine learning libraries (scikit-learn, xgboost,
catboost) follow a ".fit" and ".predict" type interface. Where the models
are trained by doing something like "model.fit(X,y)" and predictions are
made using "model.predict(X,y)" (inside python).

Unfortunately mlpack does not support such an interface which makes it
difficult for people to get familiar (people who use mlpack through
bindings and not c++ directly) with mlpack.

So I would like to propose this as an idea for GSOC 2021 that would involve
changing the bindings to support this interface.

Since I spend most of my time exploring various ML libraries inside python
(most of which support this interface), it would be an amazing experience
for me to work on this so that mlpack can also support this interface. I am
familiar with the mlpack binding system and have worked on #2787
<https://github.com/mlpack/mlpack/pull/2787> and currently working on #2868
<https://github.com/mlpack/mlpack/pull/2868>. Apart from these PR's there
are more PR's that I have worked on but these are closely related to the
project.

I request all the mentors to see if this can be a good GSOC project and if
anyone would like to mentor this.

Feedbacks are welcome from everyone.

Regards
Nippun Sharma
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