February 2018
Beginner to intermediate
258 pages
5h 47m
English
Content preview from R Deep Learning Projects
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Bi-directional LSTM networks
Well, our model did not quite work before with simple feed-forward networks. In this section, we will try a different model: Bi-directional LSTM networks.
Recall that LSTM networks preserve parts of the previous information via the hidden state. However, this information is only about the past.
Bidirectional LSTM run both ways—from past to future and back! The LSTM that runs backwards preserves information from the future. Using the two hidden states combined, you are able to keep the context of both past and future. Clearly this would not make sense for stock price prediction! Their use was initially justified in the domain of speech recognition because, as you might know from experience, the context of the ...
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.