As a philosophy grad myself, there's nothing preventing me, from improving my mathematical understanding other than my interest and motivation.

More philosophically, if understanding machine learning requires understanding mathematics, what do I mean by 'machine learning' if I don't understand mathematics? Practically speaking, if learning machine learning entails learning mathematics, then the mathematics is just more learning.

My advice, don't look at it through an academic lens of prerequisites and required courses. Just jump in and see if it sticks. Beginning is beginning.

I just started working on a blog post series exactly with this in mind. I'm focusing on Neural Networks.

Are there any particular subjects you would be interested in?

I've worked on systems for consumer goods/products companies and one thing that's consistently come up is the need to do demand planning and some forward looking sales analytics. In a number of cases we needed to do analysis based on product mix/category, consumer profiles (age, gender, color preferences, etc), or even geographic weather events that might influence sales spikes. We had humans doing this full time at the places where I worked.

This has always felt like the kind of task that would be perfect for ML-type systems/algorithms, but I haven't figured out a good way to mentally map the problem space onto ML because I'm just not super familiar with the ML topics and, as I mentioned, the mathematics has always turned me off.

What do you mean by 'machine learning?'