Basic probability is very helpful: Expectation, Standard deviation, P(A and B) = P(A)*P(B) is A and B are independent, P(A or B) = P(A)+P(B) if A and B are mutually exclusive. Also, knowing algebra is very helpful.
In a way, you don't really need to know much more because there is a lot of good software out there.
If you want to learn more math, learn Linear Regression, Logistic Regression, p-values, probability density functions, cumulative density function, the Central Limit Theorem, Gaussian Distributions, Exponential Distributions, Binomial Distribution, (maybe) Student-T distribution.
If you want to learn even more, first learn matrices (adding, multiplying, inverting, rank, span, matrix decomposition (SVD, and eigendecomposition are the most important)).
If you want to learn even more, it's time to learn calculus. Integral calculus is needed for continuous probability distributions and information theory. Differential calculus is needed to understand back propagation.
There are a lot of other good suggestions written by the other commentators.
In a way, you don't really need to know much more because there is a lot of good software out there.
If you want to learn more math, learn Linear Regression, Logistic Regression, p-values, probability density functions, cumulative density function, the Central Limit Theorem, Gaussian Distributions, Exponential Distributions, Binomial Distribution, (maybe) Student-T distribution.
If you want to learn even more, first learn matrices (adding, multiplying, inverting, rank, span, matrix decomposition (SVD, and eigendecomposition are the most important)).
If you want to learn even more, it's time to learn calculus. Integral calculus is needed for continuous probability distributions and information theory. Differential calculus is needed to understand back propagation.
There are a lot of other good suggestions written by the other commentators.