What's the Machine learn?

01.What's the learning?

learning one learning two

what's the kill?

improve some performance measure
提高一些绩效

从Data出发，经过机器的学习，得到技能的加强

Kill KILL=量化投资

Why use machine learning?

of example

这张图里面是什么？

这张图里面是什么？

如何定义树？如何让程序识别树？

你是这么认识树的？
不是你父母告诉你特征而是你的观察
而是你看来很多树(●'◡'●)
你眼睛的观察

1.exists some 'underlying pattern' to be learned
--so 'performance measure' can be improved
2.but no programmable(easy)definition
--so 'ML' is needed
3.somehow there is data about the pattern
--so ML has some 'inputs' to learn from

看看冰山一角ML的应用

01.Food(Sadilek et al.2013)
data:Twitter data(words+location)
skill:tell food poisoning likeliness of restaurant properly
2.Clothing(Abu-Mostafa,2012)
data:sales figures + client surveys
skill:give good fashion recommendations to clients
3.Housing(Tsansa and Xifara,2012)
data:characteristics of buildings and their energy load
skill:predict energy load of other buildings clousely
4.Transportation(Stallkamp et al,2012)
data:some traffic sign images and meanings
skill:recognize traffic signs accurately

ML is everywhere!

A Possible ML Solution

answer correctly ≈ [recent strngth of student > difficulty of question]
1.give ML 9 million records form 3000 students
2. ML determines (reverse-engineers)strength and difficulty automatically

电影推荐系统构想

特征

特征

机器学习深入：

example:
用户信用评估&行用卡发行：
data:

data

Basic Notations

ML输入X
ML输出Y
目标函数F
data

Data <=> training examples: D={(x1,x1),(x2,y2).....(Xn,Yn)}
(historical records in bank)

hypothesis
G:x->y

ML ML NOTE ML ML