I think there's a ton of interesting cross over between machine learning, statistics, linear algebra, real analysis, topology etc. In the sense that there exist

I think there's a ton of interesting cross over between machine learning, statistics, linear algebra, real analysis, topology etc. In the sense that there exists theorems and methods in different areas of math that are essentially the same, just different interpretations. It would be fascinating to see an exposition of this, for instance here is the geometrical interpretation of x,y,z, but actually this is the same as this theorem in calculus based statistics, except for this case... I bring this up because there is already a ton of content about popular topics, but little that goes deep and draws parallels between disparate (not that those areas I outlined are really disparate) areas of math. Even more interesting would be to choose common areas used in industry, like machine learning, and bring in some parallels and depth from fields that are not really studied outside an academic setting. But then again your audience for this is rather small