You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Product typeBook

Published inJan 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781838826994

Edition2nd Edition

Languages

Python

Tools

Keras TensorFlow

Concepts

Deep Reinforcement Learning

Author (1)

Maxim Lapan

Seq2seq training

That's all very interesting, but how is it related to RL? The connection lies in the training process of the seq2seq model, but before we come to the modern RL approaches to the problem, I need to say a couple of words about the standard way of carrying out the training.

Log-likelihood training

Imagine that we need to create a machine translation system from one language (say, French) into another language (English) using the seq2seq model. Let's assume that we have a good, large dataset of sample translations with French-English sentences that we're going to train our model on. How do we do this?

The encoding part is obvious: we just apply our encoder RNN to the first sentence in the training pair, which produces an encoded representation of the sentence. The obvious candidate for this representation is the hidden state returned from the last RNN application. At the encoding stage, we ignore the RNN's outputs, taking into account only...

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Deep Reinforcement Learning Hands-On. - Second Edition

Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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You're reading from Deep Reinforcement Learning Hands-On. - Second Edition

Seq2seq training

Log-likelihood training

Unlock this book and the full library FREE for 7 days

Author (1)

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