课程一(Neural Networks and Deep Learning),第三周(Shallow neural networks)—— 2、Practice Questions

-----------------------------------------------------------------------------------------------------------------------

-----------------------------------------------------------------------------------------------------------------------

-----------------------------------------------------------------------------------------------------------------------

import numpy as np
A=np.random.randn(4, 3)
B=np.sum(A, axis=1, keepdims=True) # axis=1时,按照行计算; axis=0时,按照列计算
print("A="+str(A))
print("B="+str(B)) result:
A=[[-0.02149271 -1.0911196 -0.63240592]
[-0.11458854 -0.18210595 0.82210656]
[ 0.39105364 -0.97201463 -0.71820102]
[ 0.30185741 -0.50767254 -0.73277816]]
B=[[-1.74501822]
[ 0.52541207]
[-1.29916201]
[-0.93859329]]
-----------------------------------------------------------------------------------------------------------------------

------------------------------------------------------------------------------------------------------------------

-------------------------------------------------------------------------------------------------------------------

-------------------------------------------------------------------------------------------------------------------


-------------------------------------------------------------------------------------------------------------------

-------------------------------------------------------------------------------------------------------------------
答案仅供参考
课程一(Neural Networks and Deep Learning),第三周(Shallow neural networks)—— 2、Practice Questions的更多相关文章
- 吴恩达《深度学习》-第一门课 (Neural Networks and Deep Learning)-第三周:浅层神经网络(Shallow neural networks) -课程笔记
第三周:浅层神经网络(Shallow neural networks) 3.1 神经网络概述(Neural Network Overview) 使用符号$ ^{[
- 【面向代码】学习 Deep Learning(三)Convolution Neural Network(CNN)
========================================================================================== 最近一直在看Dee ...
- 课程一(Neural Networks and Deep Learning),第二周(Basics of Neural Network programming)—— 4、Logistic Regression with a Neural Network mindset
Logistic Regression with a Neural Network mindset Welcome to the first (required) programming exerci ...
- 课程一(Neural Networks and Deep Learning),第一周(Introduction to Deep Learning)—— 2、10个测验题
1.What does the analogy “AI is the new electricity” refer to? (B) A. Through the “smart grid”, AI i ...
- 课程一(Neural Networks and Deep Learning),第一周(Introduction to Deep Learning)—— 1、经常提及的问题
Frequently Asked Questions Congratulations to be part of the first class of the Deep Learning Specia ...
- 课程一(Neural Networks and Deep Learning),第二周(Basics of Neural Network programming)—— 3、Python Basics with numpy (optional)
Python Basics with numpy (optional)Welcome to your first (Optional) programming exercise of the deep ...
- 课程一(Neural Networks and Deep Learning),第一周(Introduction to Deep Learning)—— 0、学习目标
1. Understand the major trends driving the rise of deep learning.2. Be able to explain how deep lear ...
- 课程一(Neural Networks and Deep Learning),第二周(Basics of Neural Network programming)—— 0、学习目标
1. Build a logistic regression model, structured as a shallow neural network2. Implement the main st ...
- 课程一(Neural Networks and Deep Learning),第二周(Basics of Neural Network programming)—— 2、编程作业常见问题与答案(Programming Assignment FAQ)
Please note that when you are working on the programming exercise you will find comments that say &q ...
- 课程一(Neural Networks and Deep Learning),第二周(Basics of Neural Network programming)—— 1、10个测验题(Neural Network Basics)
--------------------------------------------------中文翻译---------------------------------------------- ...
随机推荐
- 学习fortran77基础语法
Program ParamaterDefine Implicit None C FORTRAN变量名和关键字不区分大小写.但调用外部函数的话,需要在编译选项里指定 c 大小写等选项 因为链接器是区分大 ...
- Mybatis-Plus 实战完整学习笔记(四)------全局参数配置
一.全局配置设置 (1)全局配置Id自动生成 <!--定义mybatisplus全局配置--> <bean id="globalConfig" class=&qu ...
- 利用JDK自带的keytool生成SSL证书然后导入到SpringBoot
一:生成命令如下(这一步生成的暂不知道干嘛用的) E:\Desktop\Documents\证书>keytool -genkey -alias tomcat -keypass - -validi ...
- php7注意事项
1. 不要使用 mysql_ 函数 这一天终于来了,从此你不仅仅“不应该”使用mysql_函数.PHP 7 已经把它们从核心中全部移除了,也就是说你需要迁移到好得多的mysqli_函数,或者更灵活的 ...
- 关于在Silverlight中添加图片的问题
在Silverlight中添加图片,目前支持的Image格式有jpg和png两种,如何在目录中添加,有些什么技巧呢? <StackPanel Background="White&quo ...
- 【转】Javascript基本类型和引用类型的区别
根据[转贴]进一步补充 今天明白了一个困扰很久的问题:引用类型和基本类型的区别与联系要明白这个问题,首先需要理解堆栈的概念.那什么又是堆栈,有什么区别和联系呢?堆:首先堆是动态分配的,JVM并不会自动 ...
- stm32常识
cmsis全称Cortex Microcontroller Software Interface Standard,就是Cortex微处理器软件接口标准 stm32每组gpio有7组端口,分别是2个3 ...
- 5、Makefile基础知识汇总(转自陈皓总述)
一.Makefile里有什么? Makefile里主要包含了五个东西:显式规则.隐晦规则.变量定义.文件指示和注释. 1.显式规则.显式规则说明了,如何生成一个或多的的目标文件.这是由Makefile ...
- Android-Kotlin-区间与for&List&Map简单使用
区间与for: package cn.kotlin.kotlin_base04 /** * 区间与for */ fun main(args: Array<String>) { /** * ...
- hdu 1.2.6
勾股定理... #include<cstdio> #include<algorithm> using namespace std; int main() { //freopen ...