import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split [] from keras.datasets import fashion_mnist (train_X, train_y), (test_X, test y) = fashion_mnist.load_data() fig = plt.figure(figsize=(10,7)) for i in range (15): ax fig.add_subplot (3, 5, i+1) ax.imshow (train_X[i], cmap= 'viridis') ax.set_title('Label (y): {y}'.format(y=train_y[i])) plt.axis ('off') Label (y): 9 Label (y): 2 Label (y): 0 Label (y): 3 TIXX Label (y): 0 Label (y): 7 Label (y): 2 Label (y): 5 Label (y): 0 Label (y): 5
import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split [] from keras.datasets import fashion_mnist (train_X, train_y), (test_X, test y) = fashion_mnist.load_data() fig = plt.figure(figsize=(10,7)) for i in range (15): ax fig.add_subplot (3, 5, i+1) ax.imshow (train_X[i], cmap= 'viridis') ax.set_title('Label (y): {y}'.format(y=train_y[i])) plt.axis ('off') Label (y): 9 Label (y): 2 Label (y): 0 Label (y): 3 TIXX Label (y): 0 Label (y): 7 Label (y): 2 Label (y): 5 Label (y): 0 Label (y): 5
New Perspectives on HTML5, CSS3, and JavaScript
6th Edition
ISBN:9781305503922
Author:Patrick M. Carey
Publisher:Patrick M. Carey
Chapter3: Designing A Page Layout: Creating A Website For A Chocolatier
Section3.3: Visual Overview: Layout With Positioning Styles
Problem 4QC
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Please implement Multinomial Logistic Regression on the following data. Please continue from the given code:
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