I don't think these edits are useful. I also think that there are a couple of overlapping problems which are at work.
The tag description for machine-learning is
Methods and principles of building 'computer systems that try to automatically improve with experience.'
which is not obviously distinct from a neural-network. A novice in the field could reasonably think of the two terms as interchangeable, and I think that is exactly what's caused this user to start adding the machine-learning tag to neural-networks questions.
In my view, "machine learning" is the popular name for what Hastie et al call "statistical learning" in their landmark book Elements of Statistical Learning. Statistical learning, and its synonym "machine learning," both include neural networks as a special case.
I think the machine-learning description sounds a lot more like reinforcement-learning, which strives to create self-teaching algorithms to learn from experience, than it describes statistical learning.
I don't think it makes sense to apply a more general tag when a more specific tag is sufficient. Elements of Statistical Learning discusses cubic splines, and you can use splines in a machine learning project, but I wouldn't add the machine-learning tag to a question solely about splines.
On the other hand, the machine-learning tag is useful if you're asking a soft question, or a question about the general field. For example, the question "Why is cross-validation important in machine learning?" does not need to be concerned with random forest or SVMs or neural networks in particular. Likewise, "What is overfitting and how do you measure it?" is a question generally about statistical learning and not any specific method.
The edit queue doesn't seem to be working. In my view, these edits add irrelevant tags, which is a reason to reject; however a number of these edits were approved anyway.
The overall usage of the machine-learning tag needs some attention. The usage varies from reinforcement-learning to neural-networks to general statistics questions. I don't know what the best way is to make this tag useful; a large part of the problem is machine learning has become a marketing buzzword that means, essentially, "One of our employees did statistics on a computer." I think it would be technically correct but quixotic to force the usage of "statistical learning" in the place of "machine learning." Moreover, such a move might give people the impression that "machine learning" is not on-topic here, which is something we already have enough trouble with.
My questions for the community are
A. What, if anything, needs to be done to improve the description of the machine-learning tag?
B. What should be done to improve the usage of the machine-learning tag?
C. How can we best educate reviewers to thoughtfully consider edits which propose adding irrelevant tags?