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Hands-On Predictive Analytics with Python
book

Hands-On Predictive Analytics with Python

by Alvaro Fuentes
December 2018
Beginner to intermediate content levelBeginner to intermediate
330 pages
8h 32m
English
Packt Publishing
Content preview from Hands-On Predictive Analytics with Python

Building the MLP for predicting diamond prices

As we said before, neural network models consist of a number sequential layers, which is why Keras has a class called Sequential that we can use to instantiate a neural network model:

from keras.models import Sequentialnn_reg = Sequential()

Good! We have created an empty neural network called nn_reg. Now, we have to add layers to it. We will use what is known as fully connected or dense layers—these are layers made of neurons that are connected with all neurons from the previous layer. In other words, every neuron in a dense layer receives the output of all the neurons from the previous layer. Our MLP will be made of dense layers. Let's import the Dense class:

from keras.layers import Dense
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Publisher Resources

ISBN: 9781789138719Supplemental Content