The server’s previous technical issues have caused the loss of images and data.

基础的神经单元

The server’s previous technical issues have caused the loss of images and data.

— 空 —

​ 这个春节对于每个国人来说，都是一个不一样的春节。各大旅游景点空了，货架上的口罩品类空了，正月的拜年日程空了，城市空了，人心却没有空。全世界都在为武汉加油，为中国加油。

— 数字 —

​ 2月4日0—24时，31个省（自治区、直辖市）和新疆生产建设兵团报告新增确诊病例3887例（湖北省3156例），新增重症病例431例（湖北省377例），新增死亡病例65例（湖北省65例），新增治愈出院病例262例（湖北省125例），新增疑似病例3971例（湖北省1957例）。
　　截至2月4日24时，国家卫生健康委收到31个省（自治区、直辖市）和新疆生产建设兵团累计报告确诊病例24324例（海南省核减1例），现有重症病例3219例，累计死亡病例490例，累计治愈出院病例892例（海南省、湖北省各核减1例），现有疑似病例23260例。
　　目前累计追踪到密切接触者252154人，当日解除医学观察18457人，现有185555人正在接受医学观察。
　　累计收到港澳台地区通报确诊病例39例：香港特别行政区18例（死亡1例），澳门特别行政区10例，台湾地区11例。
——援引自国家卫生健康委员会官方网站

​ 24小时实时更新的数字背后，是对患病者的祈祷，是对康复者的祝福，是对离世者的哀悼，更是对无私奉献的医护人员和支援企业及个人的敬礼。

2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people. The latest situation summary updates are available on CDC’s web page 2019 Novel Coronavirus, Wuhan, China

from https://www.cdc.gov/coronavirus/2019-ncov/about/index.html

Lead

As everyone knows, the serious coronavirus is attacking our country especially in Wuhan while most activities are canceled. Staying at home become the daily routine. Besides working on learning stuff, I am trying to learn Python, a popular programming language which I should master long before.

After learning Matrix Linear Regression, an powerful and beginner-friendly algorithm used for predicting, I got an idea: forecasting the future trend by using a series of data including the number of people infected with virus. So I just started to do it and it’s time to share my computing results.

人工智能第二讲

矩阵形式的线性回归

x_11表示第一个样本的第一个值

T: 转制， 横竖向量转换

二范数就是各个数的平方和

伪逆矩阵

KNN分类算法

严重依赖于特征

图像数据处理基础

For and Else

1
2
3
4

for x in range(6):
    print(x)
    if x==2: break
else: print("over") # this line will skip if last line exists

Pass

There cannot exist any blank within for and if else. We must use pass to avoid the mistake.

1
2
3

for x in [1,2,3,4]:
	pass
print("over")

人工智能第一讲

定义

基于已知的函数模型预测未知的

分类

监督学习

• 需要人工标记
• 预测、推荐、标注、识别等
• 回归
• 分类

无监督学习

• 聚类
• 社团划分
• 生成学习
• 强化学习： 根据结果回馈优化模型

有监督模型

样本二元组：(x,y)

利用样本求解模型最佳参数

线性回归

• hyperparameter

What’s new for me

• Do not need to declare variables
• indentation replaces curly braces to divide code blocks

Grammar

Assigning value to multiple variables

1

x, y, z = 1, 2, "hello"

Define a global variable in local function

1
2
3

def myfunc():
	global x
	x = "fantastic"

Change the value of a global variable inside the function

1
2
3
4

x = "declan"
def myfunc():
	global x
	x = "declan and jessica"