向量点乘 (dot) 和对应分量相乘 (multiply) ：
>> a
array([1,2,3])
>>> b
array([ 1.,1.,1.])
>>> np.multiply(a,b)
array([ 1.,2.,3.])
>>> np.dot(a,b)
6.0矩阵乘法 (dot) 和对应分量相乘 (multiply) ：
>> c
matrix([[1,3]])
>>> d
matrix([[ 1.,1.]])
>>> np.multiply(c,d)
matrix([[ 1.,3.]])
>>> np.dot(c,d)
Traceback (most recent call last):
File "",line 1,in
ValueError: shapes (1,3) and (1,3) not aligned: 3 (dim 1) != 1 (dim 0) 写代码过程中，*表示对应分量相乘 (multiply) ：
>> a*b
array([ 1.,3.])
>>> c*d
Traceback (most recent call last):
File "",in
File "C:\ProgramData\Anaconda3\lib\site-packages\numpy\matrixlib\defmatrix.py",line 343,in __mul__
return N.dot(self,asmatrix(other))
ValueError: shapes (1,3) not aligned: 3 (dim 1) != 1 (dim 0)