Applied Machine Learning: Deep Learning for Industry/

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Mapping

Mapping

Transform each individual observation in a dataset through mapping.

We'll cover the following...

Chapter Goals:

  • Learn how to map a function onto each observation of a dataset
  • Implement a function that creates a dataset of serialized protocol buffers and parses each observation

A. Mapping function

After initially creating a dataset from NumPy arrays or files, we oftentimes want to apply changes to make the dataset observations more useful. For example, we might create a dataset from heights measured in inches, but we want to train a model on the heights in centimeters. We can convert each observation to the desired format by using the map function.

Python 3.5
import numpy as np
import tensorflow as tf
data = np.array([65.2, 70. ])
d1 = tf.data.Dataset.from_tensor_slices(data)
d2 = d1.map(lambda x:x * 2.54)
print(d2)

In the example above, d1 is a dataset containing the height values from data, measured in inches. We ...