Homework--0330--numpy
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
np.random.seed(sum(map(ord, "aesthetics")))
def sinplot(flip=1):
x = np.linspace(0, 14, 100)
for i in range(1, 7):
plt.plot(x, np.sin(x + i * .5) * (7 - i) * flip)
sinplot()
plt.show()Homework--0330-- pandas
import pandas as pd
from pandas import Series, DataFrame
data = {"name":["yahoo","google","facebook"], "marks":[200,400,800], "price":[9, 3, 7]}
f1 = DataFrame(data)
print f1Example--0330--pandas
# coding=UTF-8
import pandas as pd
import numpy as np
num_friends = pd.Series([100,49,41,40,25,21,21,19,19,18,18,16,15,15,15,15,14,14,
13,13,13,13,12,12,11,10,10,10,10,10,10,10,10,10,10,10,
10,10,10,10,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,8,8,8,
8,8,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,
6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,
5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,
4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2
,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1])
num_newFriends = pd.Series(np.sort(np.random.binomial(203,0.06,204))[::-1]) #用A series去建立B series
df_friendsGroup = pd.DataFrame({"A":num_friends,"B":num_newFriends}) #將兩張series合成為一個DataFrame
print("印出Col A")
print(df_friendsGroup["A"])
print("印出Col A及Col B的前10row")
select = df_friendsGroup[["A", "B"]]
print(select.head(10))
print("印出row5")
print(df_friendsGroup.ix[5])
print("印出row5~row9")
print(df_friendsGroup[5:10])Example--0406--Probability
def plot_normal_pdfs(plt):
xs = [x / 10.0 for x in range(-50, 50)]
plt.plot(xs, [normal_pdf(x, sigma=1) for x in xs], '-', label='mu=0,sigma=1')
plt.plot(xs, [normal_pdf(x, sigma=0.1) for x in xs], '--', label='mu=0,sigma=0.1')
plt.plot(xs, [normal_pdf(x, sigma=0.5) for x in xs], ':', label='mu=0,sigma=0.5')
plt.plot(xs, [normal_pdf(x, mu=-1) for x in xs], '-.', label='mu=-1,sigma=1')
plt.plot(xs, [normal_pdf(x, mu=3, sigma=0.5) for x in xs], '-.', label='mu=3,sigma=0.5')
plt.plot(xs, [normal_pdf(x, mu=-2) for x in xs], '-.', label='mu=-2,sigma=1')
plt.legend()
plt.show()
a1=0
a2=0
aboth=0
n=10000
random.seed(2)
for _ in range(n):
get1 = random_ball()
get2 = random_ball()
if get1=="B":
a1 +=1
if get1=="B" and get2=="B":
aboth +=1
if get2=="B":
a2 +=1
print "P(both):",aboth/n
print "P(get1):", a1 / n
print "P(get2):", a2 / n
print "P(get1,get2):", a1*a2/n / n
print "P(get1|get2)=p(both)/p(get2)=",(aboth/n)/(a2/n)
print "P(get1|get2)=P(get1,get2)/p(get2)=P(get1)p(get2)/p(get2)=P(get1)", (a1 / n)Example--0406--Hypothesis and Inference
p=0.99
a=0.46
mu_0, sigma_0 = normal_approximation_to_binomial(1000, a)
print("mu_0", mu_0)
print("sigma_0", sigma_0)
print("normal_two_sided_bounds("+str(p)+", mu_0, sigma_0)", normal_two_sided_bounds(p, mu_0, sigma_0))
print
HOMEWORK1--0413--gradient-descent
範例-1 THE IRIS 鳶尾花資料集
HOMEWORK2--0413--gradient-descent
範例-2 標準化數據模型
CH4. Linear Algebra
CH6. Probability
CH8. Gradient Descent
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent