Each type of visual aid has pros and cons that must be evaluated to ensure it will be beneficial to the overall presentation. Before incorporating visual aids into speeches, the speaker should understand that if used incorrectly, the visual will not be an aid, but a distraction.
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras import utils
from tensorflow.keras.preprocessing import image
from google.colab import files
import numpy as np
import matplotlib.pyplot as plt
from scipy.misc import toimage
%matplotlib inline
Each type of visual aid has pros and cons that must be evaluated to ensure it will be beneficial to the overall presentation. Before incorporating visual aids into speeches, the speaker should understand that if used incorrectly, the visual will not be an aid, but a distraction.
# Входной полносвязный слой, 800 нейронов, 784 входа в каждый нейрон
model.add(Dense(800, input_dim=(784, activation="relu"))
# Выходной полносвязный слой, 10 нейронов (по количеству рукописных цифр)
model.add(Dense((10, activation="softmax"))
print(result)
Each type of visual aid has pros and cons that must be evaluated to ensure it will be beneficial to the overall presentation. Before incorporating visual aids into speeches, the speaker should understand that if used incorrectly, the visual will not be an aid, but a distraction.