December 2017
Intermediate to advanced
536 pages
14h 23m
English
Content preview from TensorFlow 1.x Deep Learning Cookbook
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Neural machine translation - inference on a seq2seq RNN
In this recipe, we use the results of the previous recipe to translate from a source language into a target language. The idea is very simple: a source sentence is given the two combined RNNs (encoder + decoder) as input . As soon as the sentence concludes, the decoder will emit logit values and we greedily emit the word associated with the maximum value. As an example, the word moi is emitted as the first token from the decoder because this word has the maximum logit value. After that, the word suis is emitted, and so on:
An example of sequence models for NMT with probabilities as seen ...
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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.