The problem is because the .575 value doesn't have an exact representation in floating point encoding. The fix depends on what you have to do with the value as well as the impact of the inaccuracy.
If it is just a display problem use rounding to 3 decimals and you'll get the 0.575.
If it is because of computation inaccuracy, try keeping the value as a fraction which will be exact. You'll have to store and handle two floating point values but it will be exact. Postpone the effective division to the last moment when you need the result.
Check if the difference between the two value is relevant for your problem. For instance subtract sqrt epsilon to the value and check how much the change influences the final computation result and compare it with the required or desired precision.
Unfortunately we have to live with the limitation of real value representation in float. Using 128 bit precision floats will make the error much smaller but not null.
