26. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-3
Apple Pen
◎#跳脫字元
◎#如何print出「Jim's Apple Pen」
◎c='Jim's Apple Pen'
◎print (c)
◎#試試看 n 跟 t
26
32. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-7
>=<
◎ #關係運算式 < <= > >= == !=
◎ #Equal to (==) Not equal to (!=)
◎ #Less than (<) Less than or equal to (<=)
◎ #Greater than (>) Greater than or equal to (>=)
◎ '#關係運算式會吐出True or False
◎ a = 5 > 4
◎ print (a)
◎ b = 5 == 4
◎ print (b)
32
33. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-8
TrueFalseTrue
◎ # 邏輯運算式
◎ # and 兩者皆真為真
◎ # or 兩者有一真為真
◎ # not 否定
◎ a = True and True
◎ b = True and False
◎ c = False and False
◎ d = True or True
◎ e = True or False
◎ f = False or False
◎ g = not False
◎ print (a, b, c, d, e, f, g)
33
35. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-10
if you are True
◎# if, < = >, !=, ==
◎x, y, z = 3, 9, 6
◎if x < y > z:
◎ print("OK")
35
36. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-10
if you are True
◎# if, elif and else
◎a = -1
◎if a > 3:
◎ print ("a > 3")
◎elif a == 3:
◎ print ("a = 3")
◎else:
◎ print ("a < 3")
36
37. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-11
for you are True
◎# for item in sequence:
◎example_list =
[1,2,3,4,5,6,7,12,543,876,12,3,2,5]
◎for i in example_list:
◎ print(i)
◎for i in range(1, 10):
◎ print(i)
37
40. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-12
List
◎ ## 三倍長度
◎ print (3 * numbers)
◎ ## 分別操作list中的每個元素
◎ for i in numbers:
◎ print (i)
◎
◎ for i in numbers:
◎ print (i * 3)
40
42. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-13
List VS String
◎# String to List
◎s = "I love pokemon"
◎A_list = list(s)
◎B_list = s.split()
◎print(A_list)
◎print(B_list)
42
43. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Python快速入門小教室-14
List in List
◎a = [1,2,3,4,5] # 一行五列
◎multi_dim_a = [[1,2,3],
◎ [2,3,4],
◎ [3,4,5]] # 三行三列
◎print(a[1])
◎print(multi_dim_a[0][1])
◎# 2
43
103. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Making predictions about the future
with supervised learning
◎分類:
○目標標籤為類別category
◎迴歸:
○目標標籤為連續性數值 continuous numeric value
103
132. Hui-Chun Hung
Python程式語言起步走~
使用 Python 來做機器學習初探
Hierarchical Clustering
◎Use distance matrix as clustering criteria.
○This method does not require the number of
clusters k as an input, but needs a termination
conditionStep 0 Step 1 Step 2 Step 3 Step 4
b
d
c
e
a
a b
d e
c d e
a b c d e
Step 4 Step 3 Step 2 Step 1 Step 0
agglomerative
(AGNES)
divisive
(DIANA) 132