- Deep Learning with Keras
- Antonio Gulli Sujit Pal
- 213字
- 2021-07-02 23:58:00
Conventions
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "In addition, we load the true labels into Y_train and Y_test respectively and perform a one-hot encoding on them."
A block of code is set as follows:
from keras.models import Sequential
model = Sequential()
model.add(Dense(12, input_dim=8, kernel_initializer='random_uniform'))
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
# 10 outputs
# final stage is softmax
model = Sequential()
model.add(Dense(NB_CLASSES, input_shape=(RESHAPED,)))
model.add(Activation('softmax'))
model.summary()
Any command-line input or output is written as follows:
pip install quiver_engine
New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Our simple net started with an accuracy of 92.22%, which means that about eight handwritten characters out of 100 are not correctly recognized."
Warnings or important notes appear in a box like this.
Tips and tricks appear like this.
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