-Multivariate Calculus
-Statistics & Probability (with Calculus)
-Linear Algebra
-Optimizations
as a baseline. You'll need more as you progress.
You want to be comfortable with the math review in: http://www.deeplearningbook.org/
I'd wager to say most people on HN would drop out of an actual graduate level course on ML. These courses (from my experience) are more research oriented and less about "hacking".
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1.1 Who Should Read This Book?
This book can be useful for a variety of readers, but we wrote it with two main target audiences in mind. One of these target audiences is university students(undergraduate or graduate) learning about machine learning, including those who are beginning a career in deep learning and artificial intelligence research. The other target audience is software engineers who do not have a machine learning or statistics background, but want to rapidly acquire one and begin using deep learning in their product or platform.