January 2018
Intermediate to advanced
474 pages
10h 23m
English
Content preview from Mastering TensorFlow 1.x
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RNN for Time Series Data with TensorFlow and Keras
Time series data is a sequence of values, recorded or measured at different time intervals. Being a sequence, the RNN architecture is the best method to train models from such data. In this chapter, we will use a sample time series data set to showcase how to use TensorFlow and Keras to build RNN models.
We will cover the following topics in this chapter:
- Airline passengers time series dataset:
- Description and downloading of the dataset
- Visualizing the dataset
- Preprocessing the dataset for RNN in TensorFlow
- RNN in TensorFlow for time series data:
- SimpleRNN in TensorFlow
- LSTM in TensorFlow
- GRU in TensorFlow
- Preprocessing the dataset for RNN in Keras
- RNN in Keras for time series data: ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.