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Neural Network Projects with Python

You're reading from   Neural Network Projects with Python The ultimate guide to using Python to explore the true power of neural networks through six projects

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789138900
Length 308 pages
Edition 1st Edition
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Author (1):
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James Loy James Loy
Author Profile Icon James Loy
James Loy
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Table of Contents (10) Chapters Close

Preface 1. Machine Learning and Neural Networks 101 FREE CHAPTER 2. Predicting Diabetes with Multilayer Perceptrons 3. Predicting Taxi Fares with Deep Feedforward Networks 4. Cats Versus Dogs - Image Classification Using CNNs 5. Removing Noise from Images Using Autoencoders 6. Sentiment Analysis of Movie Reviews Using LSTM 7. Implementing a Facial Recognition System with Neural Networks 8. What's Next? 9. Other Books You May Enjoy

Model building in Python using Keras

We're finally ready to build and train our MLP in Keras.

Model building

As we mentioned in Chapter 1, Machine Learning and Neural Networks 101, the Sequential() class in Keras allows us to construct a neural network like Lego, stacking layers on top of one another.

Let's create a new Sequential() class:

from keras.models import Sequential

model = Sequential()

Next, let's stack our first hidden layer. The first hidden will have 32 nodes, and the input dimensions will be 8 (because there are 8 columns in X_train). Notice that for the very first hidden layer, we need to indicate the input dimensions. Subsequently, Keras will take care of the size compatibility of other hidden...

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