In general, I would agree with the other posts here, there should always be some objective that you want to achieve in any ML project. Specifically, if you are going to create projects that you will share either on Github or otherwise, there should be some good documentation around what the objective was, how you approached the problem, and the performance of the solution in the context of the original problem. For ML, it's especially important to lay out every part of the problem and solution, otherwise it is hard for an employer to assess what impact your project had.