Several methods have been developed to represent floating point numbers.

已经开发了几种方法来表示浮点数。

They are giant, inscrutable matrices of floating point numbers that we nudge in the direction of better performance until they inexplicably start working.

它们是无法参透的大型浮点数矩阵，我们在朝着更好的性能试探着前进，直到它们莫名其妙地运行起来。

And I'm doing some floating point arithmetic, ultimately.

最后，我在做一些浮点运算。

Plus, rounding errors are inherent in floating point computations.

另外，舍入误差是浮点计算中固有的。

Essentially value types like bytes, ints, floating points, simpler data types.

本质上是值类型，如字节、整数、浮点、更简单的数据类型。

Similarly, a double is like a floating point value.

类似地，double类似于浮点值。

There's an infinite number of floating point real numbers in the world.

世界上有无数的浮点实数。

Or maybe floating point values, like 3.14159, or other such values.

或者是浮点值，比如3.14159，或者其他类似的值。

These are called " floating point" numbers, because the decimal point can float around in the middle of number.

这些被称为“浮点”数字，因为小数点可以在数字中间浮动。

Percent f is going to be for a floating point value.

百分比f是一个浮点值。

In a 32-bit floating point number, the first bit is used for the sign of the number -- positive or negative.

在 32 位浮点数中，第一位用于数字的符号——正数或负数。

So, you have learned that in Python programming language you have 2 types of numbers, integers which are whole numbers like 10, they don't have a decimal point, and floating point numbers or floats.

所以，你已经了解到在 Python 编程语言中你有 2 种类型的数字，整数是整数，如 10，它们没有小数点，以及浮点数或浮点数。

We need to divide the weight by 0.45. q So, weight divided by 0.45 and just to refresh your memory, this division operator returns a floating point number but if we use double slashes we'll get an integer.

我们需要将权重除以 0.45。 q 所以，权重除以 0.45 只是为了刷新你的记忆，这个除法运算符返回一个浮点数，但如果我们使用双斜线，我们将得到一个整数。