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深度学习入门 : 基于Python的理论与实现
book

深度学习入门 : 基于Python的理论与实现

by 斋藤康毅
July 2018
Intermediate to advanced
310 pages
8h 21m
Chinese
Posts & Telecom Press
Content preview from 深度学习入门 : 基于Python的理论与实现
1章 Python 入门
12
>>> import numpy as np
Python
中使用
import
语句来导入库。这里的
import numpy as np
,直
译的话就是“将
numpy
作为
np
导入”的意思。通过写成这样的形式,之后
NumPy
相关的方法均可通过
np
来调用。
1.5.2
 生成NumPy数组
要生成
NumPy
数组,需要使用
np.array()
方法。
np.array()
接收
Python
列表作为参数,生成
NumPy
组(
numpy.ndarray
)。
>>> x = np.array([1.0, 2.0, 3.0])
>>> print(x)
[ 1. 2. 3.]
>>> type(x)
<class 'numpy.ndarray'>
1.5.3
 NumPy 的算术运算
下面是
NumPy
数组的算术运算的例子。
>>> x = np.array([1.0, 2.0, 3.0])
>>> y = np.array([2.0, 4.0, 6.0])
>>> x + y #
对应元素的加法
array([ 3., 6., 9.])
>>> x - y
array([ -1., -2., -3.])
>>> x * y # element-wise product
array([ 2., 8., 18.])
>>> x / y
array([ 0.5, 0.5, 0.5])
这里需要注意的是,数组
x
和数组
y
的元素个数是相同的(两者均是元素
个数为3 的一维数组)。当
x
y
的元素个数相同时,可以对各个元素进行算 ...
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Publisher Resources

ISBN: 9787115485588