weixin_46384400的博客

import numpy as npimport scipy.io as sioimport matplotlib.pyplot as pltfrom scipy.optimize import minimizedata = sio.loadmat('ex4data1.mat')raw_X = data['X']raw_y = data['y']X=np.insert(raw_X,0,values=1,axis=1)X.shapedef one_hot_encoder(raw_y):

import numpy as npimport matplotlib.pyplot as pltimport scipy.io as siodata = sio.loadmat('ex3data1.mat')dataprint(type(data))data.keys()raw_X = data['X']raw_y = data['y']print(raw_X.shape,raw_y.shape)def plot_an_image(X): ...

import numpy as npimport pandas as pdimport matplotlib.pyplot as pltpath = 'ex2data1.txt'data = pd.read_csv(path, names=['Exam 1', 'Exam 2', 'Accepted'])data.head()fig, ax = plt.subplots()ax.scatter(data[data['Accepted'] == 0]['Exam 1'], data[dat.

import numpy as npimport scipy.io as siodata = sio.loadmat('ex3data1.mat')raw_X = data['X']raw_y = data['y']X = np.insert(raw_X,0,values=1,axis=1)X.shapey = raw_y.flatten()y.shapetheta = sio.loadmat('ex3weights.mat')theta.keys()theta1 = t

import numpy as npimport pandas as pdimport matplotlib.pyplot as pltpath = 'ex2data2.txt'data = pd.read_csv(path, names=['Test 1', 'Test 2', 'Accepted'])data.head()fig, ax = plt.subplots()ax.scatter(data[data['Accepted'] == 0]['Test 1'], data[dat.

import numpy as npimport pandas as pdimport matplotlib.pyplot as pltpath = 'ex1data1.txt'data = pd.read_csv(path, names=['Population', 'Profit'])print(data.head())print(data.describe())data.plot(kind='scatter', x='Population', y='Profit', label=.

import numpy as npimport pandas as pdimport matplotlib.pyplot as pltdata = pd.read_csv('ex1data2.txt', names=['size', 'bedrooms', 'price'])print(data.head())def normalize_feature(data): return (data - data.mean()) / data.std()data = normali.