线性代数算法整理,理解线性代数核心算法

线性代数向量内积

Prerequisites:

先决条件：

Defining Vector using Numpy

使用Numpy定义向量

Learn: how to code for outer product of two vectors using am inbuilt function in numpy library?

了解：如何使用numpy库中的内置函数为两个向量的外部乘积编码？

Syntax:

句法：

numpy.outer(Vec_1, Vec_2) 向量外积的Python代码 (Python code for outer product of vectors) # Linear Algebra Learning Sequence# Outer Productimport numpy as npa = np.array([2,3,4,1])b = np.array([5,4,-6,45,7])outpro = np.outer(a,b)print('Vector A : ', a)print('Vector B : ', b)print('Outer product of Vector A and Vector B :', outpro)

Output:

输出：

Vector A : [2 3 4 1]Vector B : [ 5 4 -6 45 7]Outer product of Vector A and Vector B : [[ 10 8 -12 90 14] [ 15 12 -18 135 21] [ 20 16 -24 180 28] [ 5 4 -6 45 7]]

翻译自: https://www.includehelp.com/python/outer-product-of-vectors.aspx

线性代数向量内积