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

The deep NLP basics

Hopefully, you're excited about chatbots and their potential applications, so let's now get to the boring details of NLP building blocks and standard approaches. As with almost everything in ML, there is a lot of hype around deep NLP and it is evolving at a fast pace, so this section will just scratch the surface and cover the most common and standard building blocks. For a more detailed description, Richard Socher's online course CS224d (http://cs224d.stanford.edu) is a really good starting point.

RNNs

NLP has its own specifics that make it different from computer vision or other domains. One such feature is processing variable-length objects. At various levels, NLP deals with objects that could have different lengths; for example, a word in a language could contain several characters. Sentences are formed from variable-length word sequences. Paragraphs or documents consist of varying numbers of sentences. Such variability is not NLP-specific...

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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

The deep NLP basics

RNNs

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Author (1)

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