I have been examining a novel machine-learning framework for a seminar at uni. After some people asked me whether I would publish the results in a paper so they could see them as well, I thought I might as well put some more effort into it and make a publication out of it.
- I am not sure whether this adds any research value since I did not really do something new, I just summarized the key concepts of the framework and took example use-cases to compare their implementation with and without the framework (implementations without the comparison have been done in blog posts).
- I have recently been told that publications in a non-high-ranking journal can actually hurt your career. I do not want this to negatively affect my PhD application later this year.
My question is thus: Is it worth publishing a paper that is only an examination of a framework and a comparison with not using it?
Some technical background: the framework in question is Google's TensorFlow and I am comparing plain Python implementations of machine learning algorithms with the implementation utilizing the framework. I wanted to also briefly summarize the framework and compare it with other machine learning frameworks already out there - this is only half a page regarding performance, capability etc though, no code is compared here. Ultimately, the paper aims at people currently using Python who are not sure whether they should switch.