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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

Feature engineering

As briefly discussed in the previous chapter, Chapter 2, Predicting Diabetes with Multilayer Perceptrons feature engineering is the process of using one's domain knowledge of the problem to create new features for the machine learning algorithm. In this section, we shall create features based on the date and time of pickup, and location-related features.

Temporal features

As we've seen earlier in the section on data visualization, ridership volume depends heavily on the day of the week, as well as the time of day.

Let's look at the format of the pickup_datetime column by running the following code:

print(df.head()['pickup_datetime'])

We get the following output:

Recall that neural...

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